Study of Instructional Improvement (SII) (ICPSR 26282)
Crime Commission Rates Among Incarcerated Felons in Nebraska, 1986-1990 (ICPSR 9916)
Midlife in the United States (MIDUS 2): Cognitive Project, 2004-2006 (ICPSR 25281)
In 1994/1995, the MacArthur Midlife Research Network carried out a national survey of over 7,000 Americans aged 25 to 74. 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. A description of the study and findings from it are available at the MIDUS website.
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 = 957 pairs), and siblings (N = 950)) was conducted in 2004-2006. Guiding hypotheses, at the most general level, were that behavioral and psychosocial factors are consequential for health (physical and mental). The purpose of the Cognitive Project was to determine how cognition is related to overall mental and physical health. Specific goals were: (1) to characterize the nature and range of midlife cognitive performance, relative to those younger and older, across multiple domains in a nationally representative sample (MIDUS); and (2) to examine the relationship between biopsychosocial factors (e.g., SES, health status, health-promoting behaviors, metabolic and cardiovascular biomarkers, depression, personality, control beliefs, stressful life events) and individual differences in cognitive functioning.
The development of a cognitive battery for the second wave of testing of the Midlife Development in the United States (MIDUS) study provided an opportunity to examine the cognitive performance of young, middle-aged and older adults from a wide range of education levels in a large-scale, national sample. As part of the Cognitive Project of the MIDUS II the Brief Test of Adult Cognition by Telephone (BTACT) (Lachman & Tun, 2008; Tun & Lachman, 2006) was administered. More information about the BTACT can be found at the Brandeis website. The BTACT represents the first comprehensive cognitive battery, including measures of speed and reaction time, to be administered by telephone to a national sample across the adult years and into later life. With a response rate of over 86 percent for the cognitive testing component of the MIDUS II, a cognitive data set of unprecedented range in terms of age, gender, socioeconomic status (SES), education, and geographic diversity was produced.
Detroit Area Study and Chicago Area Study, 2004 (ICPSR 23820)
2010 Census Production Settings Demographic and Housing Characteristics (DHC) Demonstration Noisy Measurement File (ICPSR 38865)
The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS 2020 Redistricting Production Code). The NMF was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations, that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The NMF consists of the full set of privacy-protected statistical queries (counts of individuals or housing units with particular combinations of characteristics) of confidential 2010 Census data relating to the 2010 Demonstration Data Products Suite - Redistricting and Demographic and Housing Characteristics File - Production Settings (2023-04-03). These statistical queries, called "noisy measurements" were produced under the zero-Concentrated Differential Privacy framework (Bun, M. and Steinke, T [2016]; see also Dwork C. and Roth, A. [2014]) implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023]), which added positive or negative integer-valued noise to each of the resulting counts. The noisy measurements are an intermediate stage of the TDA prior to the post-processing the TDA then performs to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these 2010 Census demonstration data to enable data users to evaluate the expected impact of disclosure avoidance variability on 2020 Census data. The 2010 Census Production Settings Demographic and Housing Characteristics (DHC) Demonstration Noisy Measurement File (2023-04-03) has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).
The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2010 Census Edited File (CEF), which includes confidential data initially collected in the 2010 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) (Demonstration Data Products Suite/2023-04-03/). As these 2010 Census demonstration data are intended to support study of the design and expected impacts of the 2020 Disclosure Avoidance System, the 2010 CEF records were pre-processed before application of the zCDP framework. This pre-processing converted the 2010 CEF records into the input-file format, response codes, and tabulation categories used for the 2020 Census, which differ in substantive ways from the format, response codes, and tabulation categories originally used for the 2010 Census.
The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) --are provided.
These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.
2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File (NMF) (ICPSR 38937)
The 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing.
The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov).
The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File.
The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).
These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.
The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.
Please see the Globus "How to get Started" page for more information.
2010 Census Production Settings Redistricting Data (P.L. 94-171) Demonstration Noisy Measurement File (ICPSR 38777)
2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File, United States (ICPSR 38855)
The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022] https://doi.org/10.1162/99608f92.529e3cb9, and implemented in the DAS 2020 Redistricting Production Code). The 2020 Redistricting NMF was an intermediate output of the DAS during the execution of the algorithm to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File. The NMFs are intermediate privacy-protected outputs of the DAS; they were generated using the Census Bureau's implementation of the Discrete Gaussian Mechanism, calibrated to satisfy zero-Concentrated Differential Privacy with bounded neighbors. The NMF values, called "noisy measurements" are the output of applying the Discrete Gaussian Mechanism to counts from the 2020 Census Edited File (CEF). They are generally inconsistent with one another (for example, in a county composed of two tracts, the noisy measurement for the county's total population may not equal the sum of the noisy measurements of the two tracts' total population), and frequently negative (especially when the population being measured was small), but are integer-valued. The NMF was later post-processed as part of the DAS code to take the form of microdata and to satisfy various constraints. The NMF documented here contains both the noisy measurements themselves as well as the data needed to represent the DAS constraints; thus, the NMF could be used to reproduce the steps taken by the DAS code to produce microdata from the noisy measurements by applying the production code base.
The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data initially collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File.
The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2020 Census Redistricting Data (P.L. 94-171) Summary File --are provided.
These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.
The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.
Please see the Globus "How to get Started" page for more information.
State of Michigan: Taking Action on Flint Water Test Results, 2015-2017 (ICPSR 36955)
Electronic Monitoring of Nonviolent Convicted Felons: An Experiment in Home Detention in Marion County, Indiana, 1986-1988 (ICPSR 9587)
Enhanced Services for the Hard-to-Employ Demonstration and Evaluation Project: Rhode Island, Working Toward Wellness (ICPSR 33782)
Enhanced Services for the Hard-to-Employ Center for Employment Opportunities (CEO), New York City (ICPSR 33783)
Enhanced Services for the Hard-to-Employ Demonstration and Evaluation Project, Philadelphia, PA (ICPSR 33784)
Enhanced Services for the Hard-to-Employ Demonstration and Evaluation Project: Kansas and Missouri, Enhanced Early Head Start (ICPSR 33801)
California Work Pays Demonstration Project: County Welfare Administrative Data, 1992-1998, Public Use Version 4.1 (ICPSR 4207)
Social Capital and Children's Development: A randomized controlled trial conducted in 52 schools in Phoenix and San Antonio, 2008-2015 (ICPSR 35481)
The Social Capital and Children's Development data were collected in a study of the causal effects of social capital on levels and inequalities of children's social and cognitive development during the early elementary years. The study included 52 schools in Phoenix and San Antonio, including 3,084 first graders and their families, and over 200 teachers, with half the schools randomly selected for the intervention and half serving as controls. Children from low-income Latino families were a special focus of the study. The experimental design of this study allowed for testing of the causal role of social capital. Social capital here refers to trust and shared expectations embedded in social networks of parents, teachers, and children. For young children, social capital operates primarily through their relationships with their parents, enhancing development through mechanisms of social support and social control.
The research design was experimental: social capital was manipulated through a well-tested randomized intervention, Families and Schools Together (FAST), that enhanced social capital among parents, teachers, and children through an intensive after-school program and a 2-year follow-up program. FAST is intended to reduce parental isolation, enhance family engagement with schools, and strengthen family functioning; that is, to increase social capital between families and schools, among families, and within families to improve children's education and life-long outcomes. Key aspects of child development were assessed, including (a) social skills and problem behavior from standardized behavioral ratings by parents and teachers, and (b) grade retention, attendance rates, and third-grade reading and mathematics scores from school records. Social capital was measured with repeated surveys of teachers and parents that address the extent of social networks, parent involvement, trust, and shared expectations among parents, between parents and schools, and between parents and children. Demographic variables of this study include native language, years in the United States, date of birth/age, race/ethnicity, gender, and household composition.
Strengthening Washington DC Families (SWFP) Project, 1998 - 2004 (ICPSR 34425)
The Strengthening Washington DC Families (SWFP) Project examined the effectiveness of an evidence-based prevention program implemented on a sample of 715 families across mulitple settings in an urban area. The study area also included suburban Maryland. SWFP was set up as a true experimental design with families being randomly placed into one of four treatment conditions:
- child skills training only
- parent skills training only
- parent and child skills training plus family skills training
- minimal treatment controls
Entire families were assigned to one of the four treatment conditions. Data were collected from all family members who participated in the program. Thus the individual data files contain more than 715 records. The parent file contains 796 cases and the child file contains 961 cases.
The Strengthening Families Program is based on cognitive-behavioral social learning theory and family systems theory targeting elementary school-aged children. In this program parents receive training in parenting skills, children receive training primarily in social skills, and families receive family skills training. The aim of the program is to effectively reduce parent, child, and family risk factors for substance use and delinquency.
Cooperative Agreement for AIDS Community-Based Outreach/Intervention Research Program, 1992-1998: [United States] (ICPSR 3023)
Suicide and Risk Behaviors in an Incarcerated American Indian Population in the Northern Plains [United States], 1999-2000 (ICPSR 3925)
ANES 1982 Time Series Study (ICPSR 9042)
National Survey of Substance Abuse Treatment Services (N-SSATS), 2000 (ICPSR 3436)
The National Survey of Substance Abuse Treatment Services (N-SSATS) is designed to collect information from all facilities in the United States, both public and private, that provide substance abuse treatment. N-SSATS provides the mechanism for quantifying the dynamic character and composition of the United States substance abuse treatment delivery system. The objectives of N-SSATS are to collect multipurpose data that can be used to assist the Substance Abuse and Mental Health Services Administration (SAMHSA) and state and local governments in assessing the nature and extent of services provided and in forecasting treatment resource requirements, update SAMHSA's Inventory of Substance Abuse Treatment Services (I-SATS), analyze general treatment services trends, and generate the National Directory of Drug and Alcohol Abuse Treatment Programs and its online equivalent, the Substance Abuse Treatment Facility Locator.
Data are collected on topics including facility operation, services offered (assessment, substance abuse therapy and counseling, testing, transitional, and ancillary), primary focus (substance abuse, mental health, both, general health, other), hotline operation, Opioid Treatment Programs and medication dispensed, languages in which treatment is provided, type of treatment provided, number of clients (total and under age 18), number of beds, types of payment accepted, sliding fee scale, special programs offered, facility accreditation and licensure/certification, and managed care agreements.