Under contract to the National Institutes of Mental Health (NIMH), the Survey Research Center (SRC) has developed an integrated data base for the Collaborative Psychiatric Epidemiology (CPES) surveys: National Comorbidity Survey-Replication (NCS-R), National Survey of American Life (NSAL) and National Latino and Asian American Study (NLAAS). Heeringa, et al (2004) describe the sample designs and sample outcomes for the three CPES surveys. A general description of the survey methodology for the CPES surveys can be found in Pennell, et al. (2004).
This technical report outlines the method for integrating the design-based analysis weights and variance estimation codes for these three studies to permit analysts to approach analysis of the combined dataset as though it were a single, nationally-representative study.
The method of integrating the analysis of these three major survey programs was based on an adaptation of a multiple frame approach to estimation and inference for population characteristics (Hartley, 1962, 1974). There are several features and advantages to the method that are worth noting:
It was built on all of the study-specific weight development efforts conducted to date (Kessler et al. , 2004; Heeringa et al. 2004; Heeringa, et al. 2006).
It integrated overlapping representation of domains of the CPES survey population in a way that was mathematically transparent and easily understood by analysts of the combined data set. Given the large investments in study-specific weight development, this approach minimized the chance for conceptual or computational errors.
It was centered on the assumption that, conditional on the sample domain (e.g., block groups with 10-29.9% African American population) and the race/ethnicity of the respondent (e.g., Mexican-American), each study's sample representation based on the revised weight is proportional to the number of cases it "contributes" to the geographic domain x race/ethnicity cell.