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The Carolina Abecedarian (ABC) Project and the Carolina Approach to Responsive Education (CARE) projects consist of two consecutive longitudinal studies on the effectiveness of early childhood educational intervention for children at high risk for developmental delays and school failure. Combined, the two studies test the hypothesis that child care, home visit, and home school resource interventions can enhance cognitive and academic outcomes for children at risk for school failure due to factors such as poverty, low maternal IQ, or low parental education. These studies provide the only experimental data regarding the efficacy of child care interventions that began during early infancy and lasted until the child entered kindergarten. In addition, the data allow for tests of the efficacy of intervention during the primary grades.

Research hypotheses include:

• Within this high-risk sample, early cumulative risk will be negatively associated with young adult educational outcomes, employment outcomes, avoidance of teen parenthood, and avoidance of criminal behavior.
• Early intervention will moderate the effects of risk such that the effects of increased risk would be weaker for those who received the intervention than for those who did not.
• The early home environment would mediate any found effects for early risk and that early educational intervention would moderate the effects of the early home environment such that the effects of a poor-quality home environment would be weaker for those who received treatment compared to those who did not.

Demographic variables included in this collection: gender, age, level of education.

The social and demographic data included in this collection consist of a single data file for each decennial year between 1870 and 2000, covering 10 of the 12 Great Plains states. Information on a variety of social and demographic topics was gathered to historically characterize populations living in counties within the United States Great Plains, in terms of: (1) urban, rural, and total population, (2) vital statistics, (3) net migration, (4) age and sex, (5) nativity and ancestry, (6) education and literacy, (7) religion, (8) industry, and (9) housing and other characteristics. These data include selected material compiled as part of the United States population census. The United States Census of Population and Housing has been conducted since 1790 on a regular schedule that is decennial. The county-level social and demographic data produced by the United States government as a result constitute a consistent series of measures capturing changes in the United States population's size, composition, and other characteristics. A subset of the variables available from the short and long-form survey questionnaires of the United States Census of Population and Housing (as compiled for counties) were extracted from previously existing digital files. Besides the decennial census of the population, county-level data were drawn from an assortment of existing digital files as well as sources that were manually digitized. Other data include compilations of county-level information gathered from various federal agencies and private organizations as well as the agriculture and economic censuses. Supplementing these compilations are manually digitized consumer market data, religious data, and vital statistics, including information about births, deaths, marriage, and divorce.

The data in the Historical Demographic Data of Southeastern Europe series derive primarily from the ethnographic and archival research of Joel M. Halpern, Professor Emeritus of Anthropology at the University of Massachusetts at Amherst, in southeastern Europe from 1953 to 2006. The series is comprised of historical demographic data from several towns and villages in the countries of Bosnia, Croatia, Macedonia, Montenegro, Serbia, and Slovenia, all of which are former constituent republics of the Socialist Federal Republic of Yugoslavia. The data provide insight into the shift from agricultural to industrial production, as well as the more general processes of urbanization occurring in the last days of the Yugoslav state. With an expansive timeframe ranging from 1818 to 2006, the series also contains a wide cross-section of demographic data types. These include, but are not limited to, population censuses, tax records, agricultural and landholding data, birth records, death records, marriage and engagement records, and migration information.

This component of the series focuses exclusively on the Serbian village of Orasac and is composed of 64 datasets. These data record a variety of demographic and economic information between the years of 1824 and 1975. General population information at the individual level is available in official census records from 1863, 1884, 1948, 1953, and 1961, and from population register records for the years of 1928, 1966, and 1975. Census data at the household level is also available for the years of 1863, 1928, 1948, 1953, and 1961. These data are followed by detailed records of engagement and marriage. Many of these data were obtained through the courtesy of village and county officials. Priest book records from 1851 through 1966, as well as death records from 1863 to 1976 and tombstone records from 1975, are also available. Information regarding migrants and emigrants was obtained from the village council for the years of 1946 through 1975. Lastly, the data provide economic and financial information, including records of individual landholdings (for the years of 1863, 1952, 1966, and 1975), records of government taxation at the individual or household level (for 1813 through 1840, as well as for 1952), and livestock censuses (at both the individual and household level for the years of 1824 and 1825, and only at the individual level for the years of 1833 and 1834).

A Data Guide for this study is available as a web page and for download. The India Human Development Survey 2005 (IHDS) is a nationally representative, multi-topic survey of 41,554 households in 1,503 villages and 971 urban neighborhoods across India. Two one-hour interviews in each household covered topics concerning health, education, employment, economic status, marriage, fertility, gender relations, and social capital. Children aged 8-11 completed short reading, writing and arithmetic tests. Additional village, school, and medical facility interviews are also available.

This study, known as the Los Angeles Neighborhood Services and Characteristics data (L.A.NSC) includes data from governmental and business data sources on the characteristics of census tracts in Los Angeles County from 1980 to 2010. The unit of analysis is 1990 census tract (census tracts using 1990 census tract boundaries). The data also include crosswalks for census boundaries across census years. It is public use data.

The L.A.NSC data were assembled by the L.A.FANS projects to be used with L.A.FANS survey data restricted data versions 2, 2.5, and 3 all of which contain 1990 census tract numbers which can be linked with data in this file. However, the L.A.NSC files includes ALL census tracts in Los Angeles County, not just the 65 tracts sampled by L.A.FANS. Thus, the L.A.NSC data can be analyzed on their own without linkage to L.A.FANS survey data and provide longitudinal data on the characteristics of Los Angeles census tracts over a 30 year period.

Additional information on the data is available at the RAND website. See also:

• The L.A.NSC Database Users' Guides (The Los Angeles Neighborhood Services and Characteristics Database: Codebook and 2010 Neighborhood Services and Characteristics Database: NSC2).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of files available with this collection and consult the investigator(s) if further information is needed.

The Michigan Study of Life After Prison examined the association between neighborhood context and outcomes related to employment and recidivism among the cohort of former prisoners released on parole from Michigan state prisons in one calendar year (2003), controlling for pre-incarceration neighborhood context, local labor market conditions, and a large set of individual characteristics. The primary goals of this study were to answer two questions: (1) "Are ex-offenders who are released to more disadvantaged neighborhoods (those with greater poverty, unemployment, residential turnover, etc.) more likely to recidivate?" (2) "Are ex-offenders who are released to more disadvantaged neighborhoods less likely to gain stable employment?" This research sought to supplement available literature on prisoner reentry and criminal desistance, which the researchers posit existing literature has largely ignored the role that neighborhoods play in shaping the recidivism and employment of returning prisoners.

The 31 data files included as part of this collection are as follows:

Cleaned Data Files:

• casenotearrestsreps1-4_ICPSR-EDITED.dta: 4,932 Cases, 12 Variables
• casenotearrestsreps5-8_ICPSR-EDITED.dta: 5,302 Cases, 13 Variables
• casenotearrestsrep9_ICPSR-EDITED.dta: 2,321 Cases, 13 Variables
• casenoteemploymentreps1-4_ICPSR-EDITED.dta: 4,871 Cases, 28 Variables
• casenoteemploymentreps5-8_ICPSR-EDITED.dta: 4,754 Cases, 23 Variables
• casenoteemploymentrep9_ICPSR-EDITED.dta: 2,610 Cases, 23 Variables
• cleanedcasenoteaddressesreps1-8_ICPSR-EDITED.dta: 50,207 Cases, 72 Variables
• cleanedcasenoteaddressesrep9_ICPSR-EDITED.dta: 10,309 Cases, 69 Variables
• preprisonaddress_all_ICPSR-EDITED.dta: 5,183 Cases, 30 Variables
• preprisonaddress_all_rep9_ICPSR-EDITED.dta: 1,017 Cases, 63 Variables
• postprisads_ICPSR-EDITED.dta: 11,064 Cases, 41 Variables
• cleaned-demographics-population_ICPSR-EDITED.dta: 11,064 Cases, 57 Variables
• simplecrimhistory.dta: 11,064 Cases, 4 Variables
• popSAhistory.dta: 11,064 Cases, 8 Variables
• deathdates_ICPSR-EDITED.dta: 308 Cases, 3 Variables
• popprisonenterdates.dta: 11,064 Cases, 7 Variables
• discharge dates.dta: 7,369 Cases, 5 Variables
• parole and release dates for pop.dta: 11,064 cases, 3 Variables
• mdoc_recidivism_measures.dta: 11,064 Cases, 6 Variables
• recidivism dates from transits.dta: 11,064 Cases, 8 Variables
• recidivism from bir.dta: 11,064 Cases, 3 Variables
• sample marker.dta: 3,689 Cases, 2 Variables
• samplereps.dta: 3,689 Cases, 2 Variables
• tta_rsid_rep.dta: 1,363 Cases, 2 Variables

In 1995-1996, the MacArthur Midlife Research Network carried out a national survey of over 7,000 Americans aged 25 to 74 (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.

With support from the National Institute on Aging, an initial follow-up of the original Midlife Development in the United States (MIDUS) samples was conducted in 2004 (MIDUS 2). The daily stress and cognitive functioning projects were repeated at MIDUS 2; in addition the protocol was expanded to include biomarkers and neuroscience. In 2005, a baseline sample of 592 African Americans from Milwaukee was added to MIDUS to examine health issues in minority populations.

In 2013, a third wave (MIDUS 3) of survey data was collected on longitudinal participants. Data collection for this follow-up wave largely repeated baseline assessments (e.g., phone interview and extensive self-administered questionnaire), with additional questions in selected areas (e.g., economic recession experiences, optimism and coping, stressful life events, and caregiving). A third wave of cognitive functioning data and a second wave of the Milwaukee sample were also collected. Data collection for the daily diary, biomarkers, and neuroscience is ongoing. This dataset includes all known MIDUS decedents (N=2,533) from the Core National and Milwaukee samples as of December 2023.

The purpose of the study was to assess the impact of Latino ethnicity on pretrial release decisions in large urban counties. The study examined two questions:

• Are Latino defendants less likely to receive pretrial releases than non-Latino defendants?
• Are Latino defendants in counties where the Latino population is rapidly increasing less likely to receive pretrial releases than Latino defendants in counties where the Latino population is not rapidly increasing?

The study utilized the State Court Processing Statistics (SCPS) Database (see STATE COURT PROCESSING STATISTICS, 1990-2004: FELONY DEFENDANTS IN LARGE URBAN COUNTIES [ICPSR 2038]). The SCPS collects data on felony cases filed in state courts in 40 of the nation's 75 largest counties over selected sample dates in the month of May of every even numbered year, and tracks a representative sample of felony case defendants from arrest through sentencing. Data in the collection include 118,556 cases.

Researchers supplemented the SCPS with county-level information from several sources:

• Federal Bureau of Investigation Uniform Crime Reporting Program county-level data series of index crimes reported to the police for the years 1988-2004 (see UNIFORM CRIME REPORTS: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1998 [ICPSR 9335], UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1990 [ICPSR 9785], 1992 [ICPSR 6316], 1994 [ICPSR 6669], 1996 [ICPSR 2389], 1998 [ICPSR 2910], 2000 [ICPRS 3451], 2002 [ICPSR 4009], and 2004 [ICPSR 4466]).
• Bureau of Justice Statistics Annual Survey of Jails, Jurisdiction-Level data series for the years 1988-2004 (see ANNUAL SURVEY OF JAILS: JURISDICTION-LEVEL DATA, 1990 [ICPSR 9569], 1992 [ICPSR 6395], 1994 [ICPSR 6538], 1996 [ICPSR 6856], 1998 [ICPSR 2682], 2000 [ICPSR 3882], 2002 [ICPSR 4428], and 2004 [ICPSR 20200]).
• Bureau of Justice Statistics National Prosecutors Survey/Census data series 1990-2005 (see NATIONAL PROSECUTORS SURVEY, 1990 [ICPSR 9579], 1992 [ICPSR 6273], 1994 [ICPSR 6785], 1996 [ICPSR 2433], 2001 census [ICPSR 3418], and 2005 [ICPSR 4600]).
• United States Census Bureau State and County Quickfacts.
• National Center for State Courts, State Court Organization reports, 1993 (see NCJ 148346), 1998 (see NCJ 178932), and 2004 (see NCJ 212351).
• Bureau of Justice Statistics Felony Defendants in Large Urban Counties reports, 1992 (see NCJ 148826), 1994 (see NCJ 164616), 1996 (see NCJ 176981), 1998 (see NJC 187232), 2000 (see NCJ 202021), and 2002 (see NJC 210818).

The data include defendant level variables such as most serious current offense charge, number of charges, prior felony convictions, prior misdemeanor convictions, prior incarcerations, criminal justice status at arrest, prior failure to appear, age, gender, ethnicity, and race. County level variables include region, crime rate, two year change in crime rate, caseload rate, jail capacity, two year change in jail capacity, judicial selection by election or appointment, prosecutor screens cases, and annual expenditure on prosecutor's office. Racial threat stimuli variables include natural log of the percentage of the county population that is Latino, natural log of the percentage of the county population that is African American, change in the percentage of the county population that is Latino over the last six years and change in the percentage of the county population that is African American over the last six years. Cross-level interaction variables include percentage minority (Latino/African American) population zero percent to 15 percent, percentage minority (Latino/African American) population 16 percent to 30 percent, and percentage minority (Latino/African American) population 31 percent or higher.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) .

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) .

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) .

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) .

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.

A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.

TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".

Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).

Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.

Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.