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Updated: Apr 25, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Confidence interval estimation in R-DAS
Olga A Vsevolozhskaya1, James C Anthony1
1Michigan State University, United States.
Background:
Roughly 25 years ago, the United States National Institute on Drug Abuse (US NIDA) initiated the creation of public use datasets for its National Household Survey on Drug Abuse, since re-named the National Survey on Drug Use and Health (NSDUH). The Substance Abuse and Mental Health Services Administration (SAMHSA), which assumed responsibility for the survey in 1992, has continued and expanded this effort to make the survey data available to researchers. During 2012, SAMHSA created a "Restricted-Use Data Analysis System" (R-DAS) to provide researchers with the capability to create tabulations using restricted NSDUH variables not otherwise available on the public-use files.
Methods:
This methods focused article is intended to help potential users of R-DAS-like online data analysis systems by (i) clarifying statistical issues involving approximation of confidence intervals (CI), (ii) providing a way to estimate CI when tabular output is suppressed with an 'error message' based on confidentiality restrictions, and (iii) showing how to make pairwise comparisons of estimates not otherwise allowed.
Results:
For illustration purposes, some empirical estimates are presented on a topic of continuing of public health concern in the US namely, extra-medical use of pain relievers (generally opioids), where the drugs are being used to get high and otherwise outside the boundaries intended by prescribing clinicians.
Conclusion:
The R-DAS makes it possible to derive state-level estimates of male-female and age-related differences in incidence of extra-medical prescription pain reliever (EMPPR) use, not previously reported in peer-reviewed articles, and not available without research approaches described here.
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