This report describes the imputation procedures used in the 2011 National Survey on Drug Use and Health (NSDUH).

This report describes the statistical inference procedures used to produce design-based estimates for the 2012 National Survey on Drug Use and Health (NSDUH). These design-based estimates are presented in the 2012 national findings report detailed tables, as well as the 2012 mental health findings report and detailed tables. The report covers missingness rates, sampling error, degrees of freedom, statistical significance differences, confidence intervals, incidence estimates, and suppression of estimates with low precision.

Learn about the editing and statistical imputation procedures that were applied to respondent data for the 2022 National Survey on Drug Use and Health (NSDUH). Logical editing resolves inconsistencies or ambiguous data based on a respondent’s answers to other questions in the survey. Statistical imputation uses mathematical techniques to assign values when they are missing in the data.Introductory Chapters:An introduction, including a discussion of changes from the 2021 to 2022 survey.A description of the procedures and general principles for editing the NSDUH data.A description of the general imputation procedures used in NSDUH.Remaining chapters are descriptions of the editing and imputation for the following types of variables:Front-end demographics.Back-end demographics.Substance use.Special drugs and substance use disorder.Additional substance use, including treatment and emerging issues.Substance use risk and protective factors.Physical and mental health.Roster variables.Income.Health insurance.Pair variables.

This report describes the statistical inference procedures used to produce design-based estimates for the 2011 National Survey on Drug Use and Health (NSDUH). These design-based estimates are presented in the 2011 national findings report detailed tables, as well as the 2011 mental health findings report and detailed tables.

Learn about the editing and statistical imputation procedures that were applied to respondent data for the 2021 National Survey on Drug Use and Health (NSDUH). Logical editing resolves inconsistencies or ambiguous data based on a respondent’s answers to other questions in the survey. Statistical imputation uses mathematical techniques to assign values when they are missing in the data.Introductory Chapters:An introduction, including a discussion of changes from the 2020 to 2021 survey.A description of the procedures and general principles for editing the NSDUH data.A description of the general imputation procedures used in NSDUH.Remaining chapters are descriptions of the editing and imputation for the following types of variables:Front-end demographics.Back-end demographics.Substance use.Special drugs and substance use disorder.Additional substance use, including treatment and emerging issues.Substance use risk and protective factors.Physical and mental health.Roster variables.Income.Health insurance.Pair variables.

This report summarizes the 2018 NSDUH methods and other supporting information relevant to estimates of substance use and mental health issues, and organized into five chapters. Chapter 1 is an introduction to the report. Chapter 2 describes the survey, including information about the sample design; data collection procedures; and key aspects of data processing, such as development of analysis weights. Chapter 3 presents technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, and issues for selected substance use and mental health measures. Chapter 4 covers special topics related to prescription psychotherapeutic drugs. Chapter 5 describes other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population. Appendix A is a glossary that covers key definitions for use as a resource with the 2018 NSDUH reports and detailed tables. Appendix B provides a list of contributors to the report.

This report compares the estimated (or realized) precisions of a key set of estimates with the targets for the 2012 National Survey on Drug Use and Health (NSDUH). The report provides an overall of the 2012 sample design, describes relative standard errors and design effects, and the use of domain specific design effects for approximating standard error.

Publications Using SAMHSA DataWashington: 2010-2012 NSDUH substate estimates

Learn how to produce basic estimates with the 2022 National Survey on Drug Use and Health (NSDUH). The report describes the techniques that were used to make the 2022 NSDUH Detailed Tables and the 2022 NSDUH Annual National Report, but users may also find these techniques useful for their own research with NSDUH. The report describes the calculation of estimates and sampling errors, degrees of freedom, and the procedures for determining when low-precision estimates should be suppressed. It also includes sample code in several statistical languages that data users can modify to use in their own research.Chapters:Introduction to the report.Background on the survey design, including redesign and questionnaire changes.Prevalence estimates and how they were calculated, including specifics on various topics presented in the detailed tables.Discussion of how missing item responses of variables that are not imputed may lead to biased estimates.Discussion of sampling errors and how they were calculated.Description of degrees of freedom and how they were used to compare estimates.Discussion of how the statistical significance of differences between estimates was determined.Discussion of confidence interval estimation.Discussion of when estimates with low precision were suppressed.Appendix A contains code samples for various statistical procedures documented within the report.

This report describes the procedures used for editing interviewer-administered data in the 2011 National Survey on Drug Use and Health (NSDUH) computer-assisted interview (CAI).