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The overall goal of the Baby's First Years study is to assess the causal role played by household income in affecting children's early cognitive, socio-emotional, and brain development. Recent advances in developmental neuroscience suggest that experiences early in life have profound and enduring impacts on the developing brain. Family economic resources shape the nature of many of these experiences, yet the extent to which they affect children's development is unknown. The Baby's First Years project is the first randomized controlled trial to provide estimates of the causal impacts of unconditional cash gifts on the cognitive, socio-emotional, and brain development of infants and young children in low-income U.S. families.

Specifically, 1,000 recruited mothers of infants with incomes below the federal poverty line from four diverse U.S. communities are receiving monthly cash gift payments by debit card. Mothers were initially told the gifts would last for the first 40 months of their child's life, but we have secured funding to continue the payments for three additional years (i.e., for a total of 76 months). Parents in the high cash gift group (n=400 in the study sample) are receiving a cash gift of $333 per month ($4,000 per year), while parents in the low cash gift group (n=600) are receiving a nominal monthly gift payment of $20 ($240 per year), also for 76 months.

In order to measure the impacts of the unconditional cash gift income on children's cognitive and behavioral development, we are assessing high and low cash gift group differences at ages 4, 6, and 8 (and, for a subset of measures, we capture interim development at ages 1, 2, and 3) in measures of cognitive, language, memory, self-regulation, and socio-emotional development. In order to understand the processes by which child impacts emerge, we are measuring a host of family process measures summarized in our pre-registration chart. Our data collection points are referred to as: "baseline", "age 1", "age 2," "age 3", "age 4", "age 6", and "age 8".

Additional information on the project, survey design, sample, variables, and COVID-19 pandemic adjustments are available from:

• The User Guides for Baseline, Age 1, Age 2, Age 3, and Age 4, which are included under the "Data and Documentation" tab
• The project's website: babysfirstyears.com

The researchers request that all peer-reviewed papers using BFY Data:

• be submitted to PubMed https://publicaccess.nih.gov immediately upon acceptance for publication
• include the following citation to the data in their bibliography:

Citation

Magnuson, Katherine A., Kimberly Noble, Greg J. Duncan, Nathan A. Fox, Lisa A. Gennetian, Hirokazu Yoshikawa, and Sarah Halpern-Meekin. Baby's First Years (BFY), New York City, New Orleans, Omaha, and Twin Cities, 2018-2023. ICPSR37871-v8. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], YYYY-MM-DD. http://doi.org/10.3886/ICPSR37871.v8

• and include the following in their acknowledgements:

Acknowledgement

This research uses data from the Baby's First Years study. Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under Award Number R01HD087384 and 2R01HD087384. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This research was additionally supported by the US Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research and Evaluation; Office of Behavioral and Social Sciences Research-Office of the Director, National Institutes of Health; Andrew and Julie Klingenstein Family Fund; Annie E. Casey Foundation; Arnold Ventures; Arrow Impact; BCBS of Louisiana Foundation; Bezos Family Foundation, Bill and Melinda Gates Foundation; Bill Hammack and Janice Parmelee, Brady Education Fund; Chan Zuckerberg Initiative (Silicon Valley Community Foundation); Charles and Lynn Schusterman Family Philanthropies; Child Welfare Fund; Esther A. and Joseph Klingenstein Fund; Ford Foundation; Greater New Orleans Foundation; Heising-Simons Foundation; Holland Foundation; Jacobs Foundation; JPB Foundation; J-PAL North America; Lozier Foundation; New York City Mayor's Office for Economic Opportunity; Perigee Fund; Robin Hood Foundation; Robert Wood Johnson Foundation; Russell Sage Foundation; Sherwood Foundation; Valhalla Foundation; Weitz Family Foundation; W.K. Kellogg Foundation; and three anonymous donors.

Principal Investigators

Katherine Magnuson, PhD; University of Wisconsin-Madison, lead PI social and behavioral science

Kimberly Noble, MD, PhD; Teachers College, Columbia University, lead PI neuroscience

In alphabetical order:

Greg Duncan, PhD; University of California, Irvine

Nathan A. Fox, PhD; University of Maryland

Lisa A. Gennetian, PhD; Duke University Sanford School of Public Policy

Hirokazu Yoshikawa, PhD; New York University

Principal Investigators of Qualitative Substudy

Sarah Halpern-Meekin, PhD; University of Wisconsin-Madison

Katherine Magnuson, PhD; University of Wisconsin-Madison

Study Management

Lauren Meyer, Teachers College, Columbia University; National Project Director

Andrea Karsh, University of California, Irvine; Administrative Director

Matthew Maury, Duke University, Production and Retention Management

Study Co-Investigators

Sarah Black, PhD; University of New Orleans

William Fifer, PhD; Sackler Institute for Developmental Psychobiology, Columbia University Medical Center

Michael Georgieff, MD; University of Minnesota

Joseph Isler, PhD; Columbia University Medical Center

Debra Karhson, PhD; University of New Orleans

Alicia Kunin-Batson, PhD, University of Minnesota

Connie Lamm, PhD; University of Arkansas

Dennis Molfese, PhD; University of Nebraska, Lincoln

Victoria Molfese, PhD; University of Nebraska, Lincoln

Jennifer Mize Nelson, PhD; University of Nebraska, Lincoln

Timothy Nelson, PhD; University of Nebraska, Lincoln

Sonya Troller-Renfree, PhD; Teachers College, Columbia University

Study Data Collectors

The Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, is responsible for recruitment and baseline, age-1, age-2, and age-3 data collection waves. Starting at age-4 through age-8, SRC is responsible for tracking families and assisting site-based staff in locating families. SRC data collection operations are overseen by: Stephanie Chardoul, Director of Survey Research Operations and Piotr Dworak, Senior Survey Specialist, Survey Research Operations.

Contact

To contact the study investigators, email them at [email protected]

Website: babysfirstyears.com

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The Consumer Expenditure Survey (CE) program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 4416). This data collection contains the Diary Survey data, which was designed to obtain data on frequently purchased smaller items, including food and beverages (both at home and in food establishments), gasoline, housekeeping supplies, tobacco, nonprescription drugs, and personal care products and services. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2004 Diary release contains five sets of data files (FMLY, MEMB, EXPN, DTAB, DTAB_IMPUTE) and three processing files. The FMLY, MEMB, EXPN, DTAB, and DTAB_IMPUTE files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLY files contain CU characteristics, income, and summary level expenditures; the MEMB files contain member characteristics and income data; the EXPN files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTAB files contain the CU's reported income values or the mean of the five imputed income values in the multiple imputation method; and the DTAB_IMPUTE files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The three processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The three processing files are: (1) an aggregation scheme file used in the published consumer expenditure tables (DSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, and (3) a sample program file that contains the computer program used in Section VII "MICRODATA VERIFICATION AND ESTIMATION METHODOLOGY" of the Diary User Guide. The processing files are further explained in Section III.E.5. "PROCESSING FILES" of the same User Guide documentation. There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own questionnaire and independent sample), the quarterly Interview Survey and the Diary Survey (ICPSR 4415). This data collection contains the quarterly Interview Survey data, which was designed to collect data on major items of expense which respondents could be expected to recall for 3 months or longer. These included relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occurred on a regular basis, such as rent or utilities. The Interview Survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2004 Interview Survey release contains five groups of Interview data files (FMLY, MEMB, MTAB, ITAB, and ITAB_IMPUTE), 50 EXPN files, and four processing files.

The FMLY, MEMB, MTAB, ITAB, and ITAB_IMPUTE files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly datasets for each of these files, running from the first quarter of 2004 through the first quarter of 2005. The FMLY file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMB file contains member characteristics and income data; the MTAB file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITAB file contains income data converted to a monthly time frame and assigned to UCCs; and the ITAB_IMPUTE file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs.

The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLY or MTAB files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Each of the 50 EXPN files contains five quarters of data, directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The processing files are: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, (3) two vehicle make and model files (VEHI and CAPIVEHI), and (4) files containing sample programs (See Section VII.A. SAMPLE PROGRAM). The processing files are further explained in the Interview User Guide, Section III.F.6. "PROCESSING FILES." There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program consists of two surveys, the Diary Survey and the quarterly Interview Survey (ICPSR 29884). The Diary Survey is designed to obtain data on frequently purchased smaller items, including food and beverages, both at home and in food establishments, housekeeping supplies, tobacco, nonprescription drugs, and personal care products and services. Each consumer unit (CU) records its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents are asked to report all expenses (except overnight travel) that the CU incurs during the survey week.

The microdata in this collection are available as SAS, STATA, SPSS data sets or ASCII text and comma-delimited files. The 2009 Diary release contains five sets of data files (FMLY, MEMB, EXPN, DTAB, DTID) and three processing files. The FMLY, MEMB, EXPN, DTAB, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly data sets for each of these files.

The FMLY files contain CU characteristics, income, and summary level expenditures; the MEMB files contain member characteristics and income data; the EXPN files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTAB files contains the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. The summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The three processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The three processing files are: (1) an aggregation scheme file used in the published consumer expenditure tables (DSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, and (3) a sample program file that contains the computer program used in Section VII.A. SAMPLE PROGRAM of the Diary User Guide. The processing files are further explained in Section III.E.5. PROCESSING FILES of the same User Guide documentation. There is also a second user guide, "User's Guide to Income Imputation in the CE", which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program consists of two surveys, the quarterly Interview Survey and the Diary Survey (ICPSR 29883). The quarterly Interview survey is designed to collect data on major items of expense which respondents can be expected to recall for 3 months or longer. These include relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occur on a regular basis, such as rent or utilities. The Interview survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The microdata in this collection are available as SAS, STATA, SPSS data sets or ASCII text and comma-delimited files. The 2009 Interview release contains seven groups of Interview data files (FMLY, MEMB, MTAB, ITAB, ITAB_IMPUTE, FPAR, and MCHI), 50 EXPN files, and processing files.

The FMLY, MEMB, MTAB, ITAB, and ITAB_IMPUTE files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly data sets for each of these files, running from the first quarter of 2009 through the first quarter of 2010. The FMLY file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMB file contains member characteristics and income data; the MTAB file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITAB file contains income data converted to a monthly time frame and assigned to UCCs; and the ITAB_IMPUTE file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs.

The FPAR and MCHI datasets are grouped as 2-year datasets (2008 and 2009), plus the first quarter of the 2010. The FPAR file contains CU level data about the Interview survey, including paradata collected about the interview within the interview collection instrument (CAPI). This data includes information on the amount of time required to collect each interview and interview section, as well as other interviewer entered information about the resulting survey. The MCHI file contains data about each interview contact attempt, including reasons for refusal and times of contact. Both FPAR and MCHI files contain five quarters of data.

Each of the 50 EXPN files contains five quarters of data. The EXPN files contain data directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The processing files are: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, (3) a vehicle make file (CAPIVEHI), and (4) files containing sample programs. The processing files are further explained in the Interview User Guide, Section III.F.6. PROCESSING FILES. There is also a second user guide, "User's Guide to Income Imputation in the CE", which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 32483). This data collection contains the Diary Survey data, which was designed to obtain data on frequently purchased smaller items, including food and beverages, both at home and in food establishments, gasoline, housekeeping supplies, tobacco, nonprescription drugs, and personal care products and services. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The microdata in this collection are available as SAS, STATA, SPSS data sets or ASCII text and comma-delimited files. The 2010 Diary release contains five sets of data files (FMLY, MEMB, EXPN, DTAB, DTID) and three processing files. The FMLY, MEMB, EXPN, DTAB, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLY files contain CU characteristics, income, and summary level expenditures; the MEMB files contain member characteristics and income data; the EXPN files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTAB files contains the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. The summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The three processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The three processing files are: (1) an aggregation scheme file used in the published consumer expenditure tables (DSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, and (3) a sample program file that contains the computer program used in Section VII.A. SAMPLE PROGRAM of the Diary User Guide. The processing files are further explained in Section III.E.5. PROCESSING FILES of the same User Guide documentation. There is also a second user guide, "User's Guide to Income Imputation in the CE", which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own questionnaire and independent sample), the quarterly Interview Survey and the Diary Survey (ICPSR 32482). This data collection contains the quarterly Interview Survey data, which was designed to collect data on major items of expense which respondents could be expected to recall for 3 months or longer. These included relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occurred on a regular basis, such as rent or utilities. The Interview Survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The microdata in this collection are available as SAS, STATA, SPSS data sets or ASCII text and comma-delimited files. The 2010 Interview Survey release contains seven groups of Interview data files (FMLY, MEMB, MTAB, ITAB, ITAB_IMPUTE, FPAR, and MCHI), 50 EXPN files, and processing files.

The FMLY, MEMB, MTAB, ITAB, and ITAB_IMPUTE files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly data sets for each of these files, running from the first quarter of 2010 through the first quarter of 2011. The FMLY file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMB file contains member characteristics and income data; the MTAB file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITAB file contains income data converted to a monthly time frame and assigned to UCCs; and the ITAB_IMPUTE file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs.

The FPAR and MCHI datasets are grouped as 2-year datasets (2009 and 2010), plus the first quarter of the 2011. The FPAR file contains CU level data about the Interview survey, including paradata collected about the interview within the interview collection instrument (CAPI). This data includes information on the amount of time required to collect each interview and interview section, as well as other interviewer entered information about the resulting survey. The MCHI file contains data about each interview contact attempt, including reasons for refusal and times of contact. Both FPAR and MCHI files contain five quarters of data.

Each of the 50 EXPN files contains five quarters of data. The EXPN files contain data directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The processing files are: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, (3) a vehicle make file (CAPIVEHI), and (4) files containing sample programs. The processing files are further explained in the Interview User Guide, Section III.F.6. PROCESSING FILES. There is also a second user guide, "User's Guide to Income Imputation in the CE", which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 34441). This data collection contains the Diary Survey data, which was designed to obtain data on frequently purchased smaller items, including food and beverages (both at home and in food establishments), gasoline, housekeeping supplies, tobacco, nonprescription drugs, and personal care products and services. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2011 Diary release contains five sets of data files (FMLY, MEMB, EXPN, DTBD, DTID) and three processing files. The FMLY, MEMB, EXPN, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLY files contain CU characteristics, income, and summary level expenditures; the MEMB files contain member characteristics and income data; the EXPN files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contains the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The three processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The three processing files are: (1) an aggregation scheme file used in the published consumer expenditure tables (DSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, and (3) a sample program file that contains the computer program used in Section VII. "MICRODATA VERIFICATION AND ESTIMATION METHODOLOGY" of the Diary User Guide. The processing files are further explained in Section III.F.6. "PROCESSING FILES" of the same User Guide documentation. There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own questionnaire and independent sample), the quarterly Interview Survey and the Diary Survey (ICPSR 34442). This data collection contains the quarterly Interview Survey data, which was designed to collect data on major items of expense which respondents could be expected to recall for 3 months or longer. These included relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occurred on a regular basis, such as rent or utilities. The Interview Survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2011 Interview Survey release contains seven groups of Interview data files (FMLY, MEMB, MTBI, ITBI, ITII, FPAR, and MCHI), 50 EXPN files, and processing files.

The FMLY, MEMB, MTBI, ITBI, and ITII files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly datasets for each of these files, running from the first quarter of 2011 through the first quarter of 2012. The FMLY file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMB file contains member characteristics and income data; the MTBI file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITBI file contains income data converted to a monthly time frame and assigned to UCCs; and the ITII file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs.

The FPAR and MCHI datasets are grouped as 2-year datasets (2010 and 2011), plus the first quarter of the 2012 and contain paradata about the Interview survey. The FPAR file contains CU level data about the Interview survey, including timing and record use. The MCHI file contains data about each interview contact attempt, including reasons for refusal and times of contact. Both FPAR and MCHI files contain five quarters of data.

The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLY or MTBI files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Each of the 50 EXPN files contains five quarters of data, directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The processing files are: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, (3) a vehicle make file (CAPIVEHI), and (4) files containing sample programs. The processing files are further explained in the Interview User Guide, Section III.G.8. "PROCESSING FILES." There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. "Processing Files" of the Diary Survey Users' Guide. A second documentation guide, the "Users' Guide to Income Imputation," includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over.

The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components, each with its own questionnaire and independent sample: (1) the quarterly Interview Survey, and (2) the Diary Survey. This data collection contains the quarterly Interview Survey data, which was designed to collect data on major items of expense which respondents could be expected to recall for 3 months or longer. Items include relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occurred on a regular basis, such as rent or utilities. The Interview Survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The 2013 Interview Survey contains eight groups of Interview data files (FMLI, MEMI, MTBI, ITBI, ITII, NTAXI, FPAR, and MCHI), forty-three Detailed Expenditure (EXPN) files, and processing files. The FMLI, MEMI, MTBI, ITBI, ITII, and NTAXI files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly datasets for each of these files, running from the first quarter of 2013 through the first quarter of 2014 (with NTAXI files starting the second quarter of 2013). The FMLI file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMI file contains member characteristics and income data; the MTBI file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITBI file contains income data converted to a monthly time frame and assigned to UCCs; and the ITII file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs. The NTAXI file contains federal and state tax information for each tax unit within the CU.

The FPAR and MCHI datasets are grouped as 2-year datasets (2012 and 2013), plus the first quarter of 2014, and contain paradata about the Interview survey. The FPAR file contains CU level data about the Interview survey, including timing and record use. The MCHI file contains data about each interview contact attempt, including reasons for refusal and times of contact. Both FPAR and MCHI files contain five quarters of data.

The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLI or MTBI files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Each of the 43 EXPN files contains five quarters of data, directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. There are two types of processing files: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), and (2) a vehicle make file (CAPIVEHI). The processing files are further explained in the Interview Survey Users' Guide, Section III.H.9. "Processing Files." In addition to the primary users' guide, the Users' Guide to Income Imputation provides information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over.

The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

The Consumer Pyramids is the largest survey of households in India. The survey contains record-level data that are delivered in the form of population estimates. The survey contains multiple databases that contain population estimates on household demographics, household income and expenses, borrowing by household, and household assets. The data also contain individual-level health status, financial inclusion, education level, and caste and literacy estimates. Demographic information collected include gender, age, religion, education, and occupation.

Database Composition: The Consumer Pyramids Survey is conducted over the course of four-month periods or waves throughout the year totaling three rounds a year. This collection includes the following six databases: People of India; Household Income and Expenses; Household Amenities, Assets, and Liabilities; Household Expenses; Composition of Incomes at the member level; Composition of Incomes at the household level.

The Future of Families and Child Wellbeing Study (FFCWS, formerly known as the Fragile Families and Child Wellbeing Study) follows a cohort of nearly 5,000 children born in large, U.S. cities between 1998 and 2000. The study oversampled births to unmarried couples; and, when weighted, the data are representative of births in large U.S. cities at the turn of the century. The FFCWS was originally designed to address four questions of great interest to researchers and policy makers:

1. What are the conditions and capabilities of unmarried parents, especially fathers?
2. What is the nature of the relationships between unmarried parents?
3. How do children born into these families fare?
4. How do policies and environmental conditions affect families and children?

The FFCWS consists of interviews with mothers, fathers, and/or primary caregivers at birth and again when children are ages 1, 3, 5, 9, 15, and 22. The parent interviews collected information on attitudes, relationships, parenting behavior, demographic characteristics, health (mental and physical), economic and employment status, neighborhood characteristics, and program participation. Beginning at age 9, children were interviewed directly (either during the home visit or on the telephone). The direct child interviews collected data on family relationships, home routines, schools, peers, and physical and mental health, as well as health behaviors.

A collaborative study of the FFCWS, the In-Home Longitudinal Study of Pre-School Aged Children (In-Home Study) collected data from a subset of the FFCWS Core respondents at the Year 3 and 5 follow-ups to ask how parental resources in the form of parental presence or absence, time, and money influence children under the age of 5. The In-Home Study collected information on a variety of domains of the child's environment, including: the physical environment (quality of housing, nutrition and food security, health care, adequacy of clothing and supervision) and parenting (parental discipline, parental attachment, and cognitive stimulation). In addition, the In-Home Study also collected information on several important child outcomes, including anthropometrics, child behaviors, and cognitive ability. This information was collected through interviews with the child's primary caregiver, and direct observation of the child's home environment and the child's interactions with his or her caregiver.

Similar activities were conducted during the Year 9 follow-up. At the Year 15 follow-up, a condensed set of home visit activities were conducted with a subsample of approximately 1,000 teens. Teens who participated in the In-Home Study were also invited to participate in a Sleep Study and were asked to wear an accelerometer on their non-dominant wrist for seven consecutive days to track their sleep (Sleep Actigraphy Data) and that day's behaviors and mood (Daily Sleep Actigraphy and Diary Survey Data).

An additional collaborative study collected data from the child care provider (Year 3) and teacher (Years 9 and 15) through mail-based surveys. Saliva samples were collected at Year 9 and 15 (Biomarker file and Polygenic Scores). The Study of Adolescent Neural Development (SAND) COVID Study began data collection in May 2020 following the onset of the COVID-19 pandemic. It included online surveys with the young adult and their primary caregiver.

The FFCWS began its seventh wave of data collection in October 2020, around the focal child's 22nd birthday. Data collection and interviews continued through January 2024. The Year 22 wave included a young adult (YA) survey with the original focal child and a primary caregiver (PCG) survey. Data were also collected on the children of the original focal child (referred to as Generation 3, or G3).

In 2017, the FFCWS team announced the Fragile Families (FF) Challenge, a collaborative effort in which participants were tasked with using machine learning methods and FFCWS data (Baseline to Year 9) to build a model that would predict six key outcomes at Year 15. Materials used in the FF Challenge have been archived in this collection.

Documentation for these files is available on the FFCWS website under Data and Documentation. For details of updates made to the FFCWS data files, please see the project's Data Alerts page.

Data collection for the Future of Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations.

Below is the citation for use of the FFCWS data accessed through ICPSR. For information on additional citation requirements when using FFCWS in publications, please refer to this FAQ on the FFCWS project site.

The Head Start Family and Child Experiences Survey (FACES) has been a source of information on the Head Start program and the children and families it serves. The 2019 Head Start Family and Child Experiences Survey, or FACES 2019, is the seventh in a series of national studies of Head Start, with earlier studies conducted in 1997, 2000, 2003, 2006, 2009, and 2014. It includes nationally representative samples of Head Start programs and centers, classrooms, and children and their families during the 2019-2020 program year. Data from surveys of Head Start program and center directors and classroom teachers provide descriptive information about program policies and practices, classroom activities, and the background of Head Start staff. These data compromise the Classroom Study. A sample of these programs also provides data from parent surveys, teacher child reports, and direct child assessments as part of the Classroom + Child Outcomes Study. FACES 2019 is designed to help policymakers address current policy questions and to support programs and practitioners working with Head Start families.

According to the study design, FACES would have assessed children's readiness for school, surveyed parents, and asked teachers to provide information on children in both fall 2019 and spring 2020. In response to the COVID-19 (for coronavirus disease 2019) pandemic, however, FACES 2019 cancelled the first piece--the in-person data collection of child assessments in spring 2020. In-person classroom observations as part of the Classroom Study were also cancelled in spring 2020.

FACES is designed so that researchers can answer a wide range of research questions that are crucial for aiding program directors and policymakers. FACES 2019 data may be used to describe (1) the quality and characteristics of Head Start programs, teachers, and classrooms; (2) the changes or trends in the quality and characteristics of the classrooms, programs, and staff over time; (3) the school readiness skills and family characteristics of the children who participate in Head Start; (4) the factors or characteristics that predict differences in classroom quality; (5) the changes or trends in the children's outcomes and family characteristics over time; and (6) the factors or characteristics at multiple levels that predict differences in the children's outcomes. The study also supports research questions related to subgroups of interest, such as children with identified disabilities and children who are dual-language learners (DLLs), as well as policy issues that emerge during the study. The study addresses changes in children's outcomes and experiences as well as changes in the characteristics of Head Start classrooms over time and across the rounds of FACES. Some of the questions that are central to FACES include:

1. What are the characteristics of Head Start programs, including structural characteristics and program policies and practices?
2. What are the characteristics and observed quality of Head Start classrooms?
3. What are the characteristics and qualifications of Head Start teachers and management staff?
4. Are the characteristics of programs, classrooms, and staff changing over time?
5. What are the demographic characteristics and home environments of children and families who participate in Head Start?
6. Are family demographic characteristics and aspects of home environments changing over time?
7. How do families make early care and education decisions?
8. What are the experiences of families and children in Head Start?
9. What are the average school readiness skills and developmental outcomes of the population of Head Start children in fall and spring of the Head Start year?
10. What gains do children make during a year of Head Start?
11. Are children's school readiness skills (average skills or average gains in skills) improving over time?
12. Does classroom quality vary by characteristics of classrooms, teachers, or programs?
13. What characteristics of programs, teachers, or classrooms are associated with aspects of classroom quality?
14. Do the school readiness skills of children in fall and spring and their gains in skills vary by child, family, program, and classroom characteristics?
15. What is the association between observed classroom quality and children's school readiness skills? Between child and family characteristics and children's school readiness skills?

The User Guide provides detailed information about the FACES 2019 study design, execution, and data to inform and assist researchers who may be interested in using the data for future analyses. The following items are provided in the User Guide as appendices.

• Appendix A. Elements of the FACES Design and Key Instruments Used (and Child Outcomes Captured): FACES 1997-FACES 2019
• Appendix B. Copyright Permissions
• Appendix C. Instrument Content Matrices
• Appendix D. Instruments
• Appendix E. Spring 2020 Center/Program Codebook
• Appendix F. Spring 2020 Classroom/Teacher Codebook
• Appendix G. Fall 2019-Spring 2020 Child Codebook
• Appendix H. Descriptions of Composite Variables

The Head Start Family and Child Experiences Survey (FACES) is a periodic, ongoing longitudinal study of program performance. Successive nationally representative samples of Head Start children, their families, classrooms, and programs provide descriptive information on the population of children and families served; staff qualifications, credentials, and opinions; Head Start classroom practices and quality measures; and child and family outcomes. FACES includes a battery of child assessments across multiple developmental domains (cognitive, social, emotional, and physical).

For nearly a decade, the Office of Head Start, the Administration for Children and Families, other federal agencies, local programs, and the public have depended on FACES for valid and reliable national information on (1) the skills and abilities of Head Start children, (2) how Head Start children's skills and abilities compare with preschool children nationally, (3) Head Start children's readiness for and subsequent performance in kindergarten, and (4) the characteristics of the children's home and classroom environments. The FACES study is designed to enable researchers to answer a wide range of research questions that are crucial for aiding program managers and policymakers. Some of the questions that are central to FACES include:

1. What are the demographic characteristics of the population of children and families served by Head Start? How has the population served by Head Start changed?
2. What are the experiences of families and children in the Head Start program? How have they changed?
3. What are the cognitive and social skills of Head Start children at the beginning and end of their first year in the program? Has Head Start program performance improved over time?
4. Do the gains in cognitive and social skills that Head Start children achieve carry over into kindergarten? Do larger gains (or greater declines in problem behavior) translate into higher achievement at the end of kindergarten?
5. What are the qualifications of Head Start teachers in terms of education, experience, and credentials? Are average teacher education levels rising in Head Start?
6. What is the observed quality of Head Start classrooms as early learning environments, including the level and range of teaching and interactions, provisions for learning, emotional and instructional support, and classroom organization? How has quality changed over time? What program- and classroom-level factors are related to observed classroom quality? How is observed quality related to children's outcomes and developmental gains?

FACES also supports analyses of subgroups of interest, such as children with disabilities, dual language learners, and children who are performing above or below average on standardized assessments. Its design changes in response to emerging policy and research questions. For example, in response to the growing concern about childhood obesity, measures of children's height and weight were introduced in FACES 2006.

Measures for FACES 2006 were selected to balance the need to support comparisons to previous cohorts of FACES (particularly with respect to program performance measures) against the need to update the measurement battery and address emerging policy issues and benefits from progress in the assessment field. Many of the measures used in FACES 2006 were included in previous cohorts and they are presented below by the five major measurement sources in FACES: (1) child direct assessments; (2) parent interviews; (3) teacher interviews and survey; (4) classroom observations; and (5) program director, center director, and education coordinator interviews.

1. The child direct assessments included the major components of school readiness. They included a language screener, the Peabody Picture Vocabulary Test, Fourth Edition/Test de Vocabulario de Imagines Peabody, subtests from the Woodcock-Johnson Tests of Achievement Third Edition/Bateria III Woodcock-Munoz (letter word identification, applied problems, spelling, and word attack), a measure of early math literacy based on items from the Early Childhood Longitudinal Study, Birth and Kindergarten Cohorts math assessments (geometry, patterns, and measurement), story and print concepts, and physical measurements (height and weight). At the end of the direct child assessment, interviewers rate the child's attention, organization/impulse control, activity level, and sociability using items from the Leiter-R scales.
2. The parent interview was designed to provide Head Start with a comprehensive understanding of the families that they serve, including the demographic characteristics of households and household members, parent-child relationships and the quality of the child's home life, and parent ratings of the child's behavior problems, social skills, and competencies, levels and types of participation in the program and in other community services.
3. The Head Start teacher interview was designed to collect information about classroom and teacher characteristics related to the quality of care provided by Head Start programs. Teachers were asked about their classroom activities and use of curricula, as well as their demographic and educational background and professional experience. They also used a Web survey to rate the social skills, problem behaviors, and competencies of each FACES child in their classroom. Kindergarten teachers provided information about schools attended by Head Start children, their classrooms and school experiences using a Web survey. They also completed ratings of each FACES child's social skills, behavior problems and competencies.
4. The classroom observations were designed to measure peer interactions and the extent to which Head Start programs employed skilled teachers and provided developmentally appropriate environments and curricula for their children. The measures used included the Early Childhood Environment Rating Scale-Revised (ECERS-R), the Arnett Scale of Lead Teacher Behavior, and the Instructional Support scale from the Classroom Assessment Scoring System (CLASS). Counts of children and adults were also taken to calculate group size and child-adult ratios.
5. The Program Director, Center Director, and Education Coordinator Interviews gathered information about staffing and recruitment, teacher education initiatives and training, waiting lists and program expansion, classroom activities, curriculum, overview of program management, and parent involvement.

The User Guide provides detailed information about the FACES 2006 study design, execution, and data to inform and assist researchers who may be interested in using the data for future analyses. The following items are provided in the User Guide as appendices.

• Appendix A -- Copyright Statements
• Appendix B -- Instrument Content Matrices
• Appendix C -- Questionnaires
• Appendix D -- Center/Program Codebook
• Appendix E -- Classroom/Teacher Codebook
• Appendix F -- Child Codebook
• Appendix G -- Description of Constructed/Derived Variables

The Head Start Family and Child Experiences Survey (FACES) is a periodic, ongoing longitudinal study of program performance. Successive nationally representative samples of Head Start children, their families, classrooms, and programs provide descriptive information on the population of children and families served; staff qualifications, credentials, and opinions; Head Start classroom practices and quality measures; and child and family outcomes. FACES includes a battery of child assessments across multiple developmental domains (cognitive, social, emotional, and physical). FACES 2009 is the latest FACES cohort study and followed children from Head Start entry in fall 2009 through one or two years of program participation and to kindergarten.

For nearly a decade, the Office of Head Start, the Administration for Children and Families, other federal agencies, local programs, and the public have depended on FACES for valid and reliable national information on (1) the skills and abilities of Head Start children, (2) how Head Start children's skills and abilities compare with preschool children nationally, (3) Head Start children's readiness for and subsequent performance in kindergarten, and (4) the characteristics of the children's home and classroom environments. The FACES study is designed to enable researchers to answer a wide range of research questions that are crucial for aiding program managers and policymakers. Some of the questions that are central to FACES include:

1. What are the demographic characteristics of the population of children and families served by Head Start? How has the population served by Head Start changed?
2. What are the experiences of families and children in the Head Start program? How have they changed?
3. What are the cognitive and social skills of Head Start children at the beginning and end of their first year in the program? Has Head Start program performance improved over time?
4. Do the gains in cognitive and social skills that Head Start children achieve carry over into kindergarten? Do larger gains (or greater declines in problem behavior) translate into higher achievement at the end of kindergarten?
5. What are the qualifications of Head Start teachers in terms of education, experience, and credentials? Are average teacher education levels rising in Head Start?
6. What is the observed quality of Head Start classrooms as early learning environments, including the level and range of teaching and interactions, provisions for learning, emotional and instructional support, and classroom organization? How has quality changed over time? What program- and classroom-level factors are related to observed classroom quality? How is observed quality related to children's outcomes and developmental gains?

In response to recent trends and mandates, FACES 2009 expanded the information collected on families and children who speak a primary language other than English and the information collected on children who are homeless. Earlier cohorts of FACES gathered information on the languages spoken in the home and used for classroom instruction. Given the growth in the population of Hispanic/Latino preschoolers (Hernandez 2006), FACES 2009 placed additional emphasis on Dual Language Learners (DLLs). In addition, given the 2007 Head Start Act's focus on children and families who are homeless, FACES 2009 expanded coverage on the enrollment of such children, how the program ensures that they enroll in Head Start, and the special services available to such children and their families.

FACES 2009 carefully balanced the need for consistent measurement of outcomes against the need for improvements in instrumentation and techniques. In some instances, new instruments were added to obtain more comprehensive information on Head Start children. For example, the Expressive One-Word Picture Vocabulary Test was added to assess children's expressive language, which is related to later reading achievement even more so than receptive language (National Early Literacy Panel 2008). A measure of phonemic awareness from the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B) preschool wave was also added to assess children's knowledge of beginning and ending sounds in words. Further, FACES 2009 included a direct assessment of executive functioning-a pencil tapping task to examine children's inhibitory control, working memory, and attention-which has been shown to relate to young children's development in mathematics, vocabulary, and literacy (Blair and Razza 2007; Espy et al. 2004; McClelland et al. 2007).

The User Guide provides detailed information about the FACES 2009 study design, execution, and data to inform and assist researchers who may be interested in using the data for future analyses. The following items are provided in the User Guide as appendices.

• Appendix A - Copyright statements
• Appendix B - Instrument Content Matrices
• Appendix C - Questionnaires
• Appendix D - Center/Program Codebook
• Appendix E - Classroom/Teacher Codebook
• Appendix F - Child Codebook
• Appendix G - Description of Constructed/Derived Variables

The Housing and Children's Healthy Development (HCHD) Study included four main aims:

1. to learn how parents make choices about where to live while negotiating tradeoffs between dwelling unit quality, neighborhood quality, and school quality;
2. to assess how features of the child's social contexts--home, neighborhood, and school--combine to influence key cognitive, socio-emotional, and health outcomes among parents and their children;
3. to examine how the quality of housing affects parenting practices and outcomes for children and their caregivers; and
4. to enhance the study of child development through theoretical and methodological advances in the study of housing and the other social contexts related to housing.

For this collection, the study team conducted Wave 1 data collection with families in Cleveland, Ohio (Cuyahoga County) and Dallas, Texas, United States, using a randomized controlled trial design. One-half of the sample was an experimental sample consisting of applicants for a federal housing voucher, including both voucher winners (treatment group) and voucher losers (control group). The other half of the sample was generated through a random selection and screening process in census blocks that varied by household income weighted toward lower-income blocks.

Interviews were conducted with primary caregivers, lasting about 90 minutes, and included the collection of anthropometric measures from primary caregivers and children and administration of Woodcock-Johnson tests to children. Primary caregiver voucher sample participants were asked for three blood pressure measurements, and blood spots were collected from voucher sample primary caregivers and children. The data collection also includes laser tape measurement of all rooms in a household, 8 block face neighborhood observations, and post-interview observations. Four-day leave-behind child time diary data were collected but are not available.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The TILDA Series data files, including studies 34315, 38681, 37105, 37106, 38670, 38674, are no longer available from ICPSR and NACDA at the request of the data producer due to concerns related to EU and Irish data privacy and data sharing rules. Individuals interested in obtaining TILDA data access at this time should reach out to the TILDA project directly (https://tilda.tcd.ie/data/accessing-data/).

The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a two yearly basis with a sample cohort of 8,504 people aged 50 and over (or their spouses/partners) and resident in Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized. Demographic and background variables include age, sex, marital status, household composition, education, and employment.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The TILDA Series data, including studies 34315, 38681, 37105, 37106, 38670, 38674, are currently unavailable at the request of the data producer due to concerns related to EU and Irish data privacy and data sharing rules. We are working to determine the best solution to continue to share these data with the research community. Individuals interested in obtaining TILDA data access at this time should reach out to the TILDA project directly (https://tilda.tcd.ie/data/accessing-data/).

The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a two yearly basis with a sample cohort of 8,504 people aged 50 and over (or their spouses/partners) and resident in Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized.

The second wave of TILDA interviews were undertaken between February 2012 and March 2013. Of the 8,504 interviewed in Wave 1, a second interview was obtained for 7,445 respondents. These consisted of the self, proxy and end-of-life interviews types. In addition to the returning respondents, 170 interviews were obtained from eligible household members who had chosen not to take part in Wave 1 or the new spouses/partners of existing respondents.

Demographic and background variables include age, sex, marital status, household composition, education, and employment.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The TILDA Series data, including studies 34315, 38681, 37105, 37106, 38670, 38674, are currently unavailable at the request of the data producer due to concerns related to EU and Irish data privacy and data sharing rules. We are working to determine the best solution to continue to share these data with the research community. Individuals interested in obtaining TILDA data access at this time should reach out to the TILDA project directly (https://tilda.tcd.ie/data/accessing-data/).

The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a two yearly basis with a sample cohort of 8,504 people aged 50 and over (or their spouses/partners) and resident in Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized.

The third wave of TILDA interviews were undertaken between March 2014 and October 2015. Of the 7,445 interviewed in Wave 2, a third interview was obtained for 6,874 respondents. These consisted of the self, proxy and end-of-life interviews types. In addition to the returning respondents, 28 interviews were obtained from eligible household members who had chosen not to take part in Wave 1 or the new spouses/partners of existing respondents.

Demographic and background variables include age, sex, marital status, household composition, education, and employment.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The TILDA Series data, including studies 34315, 38681, 37105, 37106, 38670, 38674, are currently unavailable at the request of the data producer due to concerns related to EU and Irish data privacy and data sharing rules. We are working to determine the best solution to continue to share these data with the research community. Individuals interested in obtaining TILDA data access at this time should reach out to the TILDA project directly (https://tilda.tcd.ie/data/accessing-data/).

The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a one year basis with a sample cohort of residents of Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized.

The fourth wave of TILDA interviews were undertaken between January and December 2016. A total of 5,713 participants completed the self-interview.

Demographic and background variables include age, sex, marital status, household composition, education, and employment.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The TILDA Series data, including studies 34315, 38681, 37105, 37106, 38670, 38674, are currently unavailable at the request of the data producer due to concerns related to EU and Irish data privacy and data sharing rules. We are working to determine the best solution to continue to share these data with the research community. Individuals interested in obtaining TILDA data access at this time should reach out to the TILDA project directly (https://tilda.tcd.ie/data/accessing-data/).

The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a one year basis with a sample cohort of residents of Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized.

The fifth wave of TILDA interviews were undertaken between January and December 2018. A total of 4,978 participants completed the self-interview.

Demographic and background variables include age, sex, marital status, household composition, education, and employment.

This study includes public user data files of two waves of interviews with L.A.FANS respondents. There often are multiple respondents in L.A.FANS households and Wave 2 includes both panel respondents and a new sample. Users' Guides which explain the design and how to use the sample are available for Wave 1 and Wave 2 at the RAND website.

The Los Angeles Family and Neighborhood Survey (L.A.FANS) is a two-wave study of adults and children in Los Angeles County and of the neighborhoods in which they live. The first wave (L.A.FANS-1), which was fielded between April 2000 and January 2002, interviewed adults and children living in 3,085 households in a stratified probability sample of 65 neighborhoods throughout Los Angeles County. The samples of neighborhoods and individuals were representative of neighborhoods and residents of Los Angeles County. Poorer neighborhoods and households with children were oversampled. In Wave 2 of L.A.FANS (L.A.FANS-2), Wave 1 respondents living in Los Angeles County were reinterviewed and updated information was collected on Wave 1 respondents who had moved away from Los Angeles County. A sample of individuals who moved into each sampled neighborhood between Waves 1 and 2 was also interviewed, for a total of 2,319 adults and 1,382 children (ages less than 18 years). Additional information on the project is available at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes a restricted data file for Wave 1 of the L.A.FANS data. To compare L.A.FANS restricted data, version 1 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 1 (study 1). This file adds only a few variables to the L.A.FANS, Wave 1 public use files. Specifically, it adds a "pseudo-tract ID" which is a number from 1 to 65, randomly assigned to each census tract (neighborhood) in the study. It is not possible to link pseudo-tract IDs in any way to real tract IDs or other neighborhood characteristics. However, pseudo-tract IDs permit users to conduct analyses which take into account the clustered sample design in which neighborhoods (tracts) were selected first and then individuals were sampled within neighborhoods. Pseudo-tract IDs do so because they identify which respondents live in the same neighborhood. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 1 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 1 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 1 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes restricted data file, version 2, for Wave 1 of the L.A.FANS data. To compare L.A.FANS restricted data, version 2 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 1 (study 1). This file adds only a few variables to the L.A.FANS, Wave 1 public use files. Specifically, it adds the census tract number for the tract each respondent lives in. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 1 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 2 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 1 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes restricted data version 2.5, for Wave 1 of the L.A.FANS data. To compare L.A.FANS restricted data, version 2.5 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 1 (study 1). This file adds only a few variables to the L.A.FANS, Wave 1 public use files. Specifically, it adds the census tract and block number for the tract each respondent lives in. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 1 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 2.5 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 1 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes restricted data version 3, for Wave 1 of the L.A.FANS data. To compare L.A.FANS restricted data, version 3 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 1 (study 1). This file adds only a few variables to the L.A.FANS, Wave 1 public use files. Specifically, it adds the census tract and block number for the tract each respondent lives in and geographic coordinates data for a number of locations reported by the respondent (including home, grocery store, place of work, place of worship, schools, etc.). It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 1 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 3 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 1 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes public user data files of two waves of interviews with L.A.FANS respondents. There often are multiple respondents in L.A.FANS households and Wave 2 includes both panel respondents and a new sample. Users' Guides which explain the design and how to use the sample are available for Wave 1 and Wave 2 at the RAND website.

The Los Angeles Family and Neighborhood Survey (L.A.FANS) is a two-wave study of adults and children in Los Angeles County and of the neighborhoods in which they live. The first wave (L.A.FANS-1), which was fielded between April 2000 and January 2002, interviewed adults and children living in 3,085 households in a stratified probability sample of 65 neighborhoods throughout Los Angeles County. The samples of neighborhoods and individuals were representative of neighborhoods and residents of Los Angeles County. Poorer neighborhoods and households with children were oversampled. In Wave 2 of L.A.FANS (L.A.FANS-2), Wave 1 respondents living in Los Angeles County were reinterviewed and updated information was collected on Wave 1 respondents who had moved away from Los Angeles County. A sample of individuals who moved into each sampled neighborhood between Waves 1 and 2 was also interviewed, for a total of 2,319 adults and 1,382 children (ages less than 18 years). Additional information on the project is available at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes a restricted data file for Wave 2 of the L.A.FANS data. To compare L.A.FANS restricted data, version 1 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 2 (study 2). This file adds only a few variables to the L.A.FANS, Wave 2 public use files. Specifically, it adds a "pseudo-tract ID" which is a number from 1 to 65, randomly assigned to each census tract (neighborhood) in the study. It is not possible to link pseudo-tract IDs in any way to real tract IDs or other neighborhood characteristics. However, pseudo-tract IDs permit users to conduct analyses which take into account the clustered sample design in which neighborhoods (tracts) were selected first and then individuals were sampled within neighborhoods. Pseudo-tract IDs do so because they identify which respondents live in the same neighborhood. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 2 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 1 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 2 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes a restricted data file, version 2, for Wave 2 of the L.A.FANS data. To compare L.A.FANS restricted data, version 2 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 2 (study 2). This file adds only a few variables to the L.A.FANS, Wave 2 public use files. Specifically, it adds the census tract number for the tract each respondent lives in. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 2 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 2 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 2 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes a restricted data file, version 2.5, for Wave 2 of the L.A.FANS data. To compare L.A.FANS restricted data, version 2.5 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 2 (study 2). This file adds only a few variables to the L.A.FANS, Wave 2 public use files. Specifically, it adds the census tract and block number for the tract each respondent lives in. It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 2 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 2.5 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 2 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

This study includes a restricted data file, version 3, for Wave 2 of the L.A.FANS data. To compare L.A.FANS restricted data, version 3 with other restricted data versions, see the table on the series page for the L.A.FANS data here. Data in this study are designed for use with the public use data files for L.A.FANS, Wave 2 (study 2). This file adds only a few variables to the L.A.FANS, Wave 2 public use files. Specifically, it adds the census tract and block number for the tract each respondent lives in and geographic coordinates data for a number of locations reported by the respondent (including home, grocery store, place of work, place of worship, schools, etc.). It also includes certain variables, thought to be sensitive, which are not available in the public use data. These variables are identified in the L.A.FANS Wave 2 Users Guide and Codebook. Finally, some distance variables and individual characteristics which are treated in the public use data to make it harder to identify individuals are provided in an untreated form in the Version 3 restricted data file. Please note that L.A. FANS restricted data may only be accessed within the ICPSR Virtual Data Enclave (VDE) and must be merged with the L.A. FANS public data prior to beginning any analysis.

A Users' Guide which explains the design and how to use the samples are available for Wave 2 at the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

In 1995-1996, the MacArthur Midlife Research Network carried out a national survey of 7,108 Americans aged 25 to 74 (MIDLIFE IN THE UNITED STATES (MIDUS), 1995-1996 [ICPSR 2760]). The purpose of the study was to investigate the role of behavioral, psychological, and social factors in understanding age-related differences in physical and mental health. The study was innovative for its broad scientific scope, its diverse samples (which included twins and the siblings of main sample respondents), and its creative use of in-depth assessments in key areas (e.g., daily stress and cognitive functioning). A description of the study and findings from it are available at http://www.midus.wisc.edu. With support from the National Institute on Aging, a longitudinal follow-up of the original MIDUS samples: core sample (N = 3,487), metropolitan over-samples (N = 757), twins (N = 925 complete pairs), and siblings (N = 950), was conducted in 2004-2006. Guiding hypotheses for it, at the most general level, were that behavioral and psychosocial factors are consequential for physical and mental health. MIDUS 2 respondents were aged 35 to 86. Data collection largely repeated baseline assessments (e.g., phone interview and extensive self-administered questionnaire), with additional questions in selected areas (e.g., cognitive functioning, optimism and coping, stressful life events, and caregiving). To add refinements to MIDUS 2, an African American sample (N = 592) was recruited from Milwaukee, Wisconsin, who participated in a personal interview and completed a questionnaire paralleling the above assessments. Survey data for the Milwaukee sample are available in a separate project [ICPSR 22840]. Also administered was a modified form of the mail questionnaire, via telephone, to respondents who did not complete a self-administered questionnaire.

The Moving to Opportunity (MTO) program was a randomized housing experiment administered by the United States Department of Housing and Urban Development (HUD) that gave low-income families living in high-poverty areas the chance to move to lower-poverty areas. This Restricted Access Dataset (RAD) includes data from the 3,273 adults interviewed as part of the MTO long-term evaluation and is comprised of variables analyzed for the article "Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults" that was published in the journal Science on September 21, 2012. The article focused on subjective well-being, physical and mental health, social networks, neighborhoods, housing, and economic self-sufficiency. Families were tracked from the baseline survey (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families from five United States cities. Households were randomly assigned to one of three groups:

1. The low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location.
2. The traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling.
3. The control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and other social programs and services to which they would otherwise be entitled.

The dataset contains all outcomes and mediators analyzed for the Science article, as well as a variety of demographic and other baseline measures that were controlled for in the analysis. Demographic information includes age, gender, race/ethnicity, employment status, and education level.

The National Comorbidity Survey Replication Adolescent Supplement (NCS-A) was designed to estimate the lifetime-to-date and current prevalence, age-of-onset distributions, course, and comorbidity of DSM-IV disorders in the child and adolescent years of life among adolescents in the United States; to identify risk and protective factors for the onset and persistence of these disorders; to describe patterns and correlates of service use for these disorders; and to lay the groundwork for subsequent follow-up studies that can be used to identify early expressions of adult mental disorders.

The core NCS-A interview schedule was an adaptation of the World Health Organization Composite International Diagnostic Interview (CIDI). NCS-A also administered the non-verbal subtest (Matrices subtest) of the Kaufman Brief Intelligence Test (K-BIT).

In addition to interviewing adolescents, information was collected from a parent or a parent surrogate to obtain an additional perspective on the adolescent's mental health and its correlates. Information from parents focused on the five adolescent disorders for which previous methodological research has most consistently shown that parental reports are important for making diagnoses: attention-deficit/hyperactivity disorder, conduct disorder, oppositional defiant disorder, major depressive episode, and dysthymic disorder.

Demographic information collected by NCS-A includes age, citizenship status, country of birth, criminal history, ethnicity, grandparents' country of birth, language(s) spoken in the home, parents' country of birth, race, religion, and sex.

The data collection contains six data files: (1) data for the adolescent household and school respondents; (2) data for the parents who responded to the long self-administered questionnaire; (3) data for the parents who responded to both the long self-administered questionnaire and short telephone interview; (4) diagnostic variables derived from the data collected from the adolescents and parents; (5) K-BIT scores normed to the NCS-A adolescent sample; and (6) raw K-BIT data.

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999 the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The surveys examine a nationally representative sample of approximately 5,000 persons each year. These persons are located in counties across the United States, 15 of which are visited each year.

For NHANES 2003-2004, there were 12,761 persons selected for the sample, 10,122 of those were interviewed (79.3 percent) and 9,643 (75.6 percent) were examined in the mobile examination centers (MEC). Many of the NHANES 2003-2004 questions were also asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2002. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. As in past health examination surveys, data were collected on the prevalence of chronic conditions in the population. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey. Risk factors, those aspects of a person's lifestyle, constitution, heredity, or environment that may increase the chances of developing a certain disease or condition, were examined. Data on smoking, alcohol consumption, sexual practices, drug use, physical fitness and activity, weight, and dietary intake were collected. Information on certain aspects of reproductive health, such as use of oral contraceptives and breastfeeding practices, were also collected. The diseases, medical conditions, and health indicators that were studied include: anemia, cardiovascular disease, diabetes and lower extremity disease, environmental exposures, equilibrium, hearing loss, infectious diseases and immunization, kidney disease, mental health and cognitive functioning, nutrition, obesity, oral health, osteoporosis, physical fitness and physical functioning, reproductive history and sexual behavior, respiratory disease (asthma, chronic bronchitis, emphysema), sexually transmitted diseases, skin diseases, and vision. The sample for the survey was selected to represent the United States population of all ages. Special emphasis in the 2003-2004 NHANES was on adolescent health and the health of older Americans. To produce reliable statistics for these groups, adolescents aged 15-19 years and persons aged 60 years and older were over-sampled for the survey. African Americans and Mexican Americans were also over-sampled to enable accurate estimates for these groups. Several important areas in adolescent health, including nutrition and fitness and other aspects of growth and development, were addressed. Since the United States has experienced dramatic growth in the number of older people during the twentieth century, the aging population has major implications for health care needs, public policy, and research priorities. NCHS is working with public health agencies to increase the knowledge of the health status of older Americans. NHANES has a primary role in this endeavor. In the examination, all participants visit the physician who takes their pulse or blood pressure. Dietary interviews and body measurements are included for everyone. All but the very young have a blood sample taken and see the dentist. Depending upon the age of the participant, the rest of the examination includes tests and procedures to assess the various aspects of health listed above. Usually, the older the individual, the more extensive the examination. Some persons who are unable or unwilling to come to the examination center may be given a less extensive examination in their homes.

Demographic data file variables are grouped into three broad categories: (1) Status Variables: provide core information on the survey participant. Examples of the core variables include interview status, examination status, and sequence number. (Sequence number is a unique ID assigned to each sample person and is required to match the information on this demographic file to the rest of the NHANES 2003-2004 data). (2) Recoded Demographic Variables: these variables include age (age in months for persons through age 19 years, 11 months; age in years for 1- to 84-year-olds, and a top-coded age group of 85 years of age and older), gender, a race/ethnicity variable, current or highest grade of education completed, (less than high school, high school, and more than high school education), country of birth (United States, Mexico, or other foreign born), Poverty Income Ratio (PIR), income, and a pregnancy status variable (adjudicated from various pregnancy related variables). Some of the groupings were made due to limited sample sizes for the two-year data set. (3) Interview and Examination Sample Weight Variables: sample weights are available for analyzing NHANES 2003-2004 data. For a complete listing of survey contents for all years of the NHANES see the document -- Survey Content -- NHANES 1999-2010.

Downloads of Add Health require submission of the following information, which is shared with the original producer of Add Health: supervisor name, supervisor email, and reason for download. A Data Guide for this study is available as a web page and for download.

The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2018 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships.

Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents.

Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer.

From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study.

Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV).

Wave V data collection took place from 2016 to 2018, when the original Wave I respondents were 33 to 43 years old. For the first time, a mixed mode survey design was used. In addition, several experiments were embedded in early phases of the data collection to test response to various treatments. A similar range of data was collected on social, environmental, economic, behavioral, and health circumstances of respondents, with the addition of retrospective child health and socio-economic status questions. Physical measurements and biospecimens were again collected at Wave V, and included most of the same measures as at Wave IV.

The overall goal of Wave VI was to better understand life course trajectories, determinants, and consequences of critical dimensions of aging, health, and health disparities among U.S. early midlife adults. Data collection took place from 2022 to 2025, with participants between the ages of 39 and 51, with an average age of 44. Beyond longitudinal survey measures, newly added questions included those on cumulative stress, discrimination, despair, work-life balance, memory, physical limitations, and caregiving. Continuing from previous waves, home exams collected physical measurements and biospecimens with most of the same measures as Wave V.

The National Longitudinal Study of Adolescent to Adult Health (Add Health) Parent Study Public Use collection includes data gathered as part of the Add Health longitudinal survey of adolescents. The original Add Health survey is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. In Wave 1 of the Add Health Study (1994-1995), a parent of each Add Health Sample Member (AHSM) was interviewed. The Add Health Parent Study gathered social, behavioral, and health survey data in 2015-2017 from the parents of Add Health Sample members who were originally interviewed at Wave 1 (1994-1995). Wave 1 Parents were asked about their adolescent children, their relationships with them, and their own health.

The Add Health Parent Study interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In addition, survey data contains cognitive assessments, a medications log linked to a medications database lookup table, and household financial information collection. The survey also includes permission for administrative data linkages and includes data from a Family Health History Leave-Behind questionnaire. Interviews were conducted with parents' spouse/partner when available.

Research domains targeted in the survey and research questions that may be addressed using the Add Health Parent Study data include:

• Health Behaviors and Risks Many health conditions and behaviors run in families; for example, cardiovascular disease, obesity and substance abuse. How are health risks and behaviors transmitted across generations or clustered within families? How can we use information on the parents' health and health behavior to better understand the determinants of their (adult) children's health trajectories?
• Cognitive Functioning and Non-Cognitive Personality Traits What role does the intergenerational transmission of personality and locus of control play in generating intergenerational persistence in education, family status, income and health? How do the personality traits of parents and children, and how they interact, influence the extent and quality of intergenerational relationships and the prevalence of assistance across generations?
• Decision-Making, Expectations, and Risk Preferences Do intergenerational correlations in risk preferences represent intergenerational transmission of preferences? If so, are the transmission mechanisms a factor in biological and environmental vulnerabilities? Does the extent of genetic liability vary in response to both family-specific and generation-specific environmental pressures?
• Family Support, Relationship Quality and Ties of Obligation How does family complexity affect intergenerational obligations and the strength of relationship ties? As parents near retirement: What roles do they play in their children's lives and their children in their lives? What assistance are they providing to their adult children and grandchildren? What do they receive in return? And how do these ties vary with divorce, remarriage and familial estrangement?
• Economic Status and Capacities What are the economic capacities of the parents' generation as they reach their retirement years? How have fared through the wealth and employment shocks of the Great Recession? Are parents able to provide for their own financial need? And, do they have the time and financial resources to help support their children and grandchildren and are they prepared to do so?