CONTENT: The workshop will focus on small area estimation methods that use regression approaches. After a brief introduction and background that reviews the well-known limitations of traditional needs assessment methodologies, the workshop will provide an overview of major methods small area estimation, including direct estimation, indirect standardization (or weighting), and regression-based methods. Three types of regression methods will be covered, namely ones that use: (i) individual-level covariates only; (ii) individual and area level covariates (multilevel models); (iii) area-level covariates only. It will then move to the topic of access and preparation of data, using the NCS-R as a key example. The heart of the presentation will involve modeling considerations, generation of estimates, and the calculation of confidence intervals, and the testing of estimates using independent sources of data. Recommendations for software will also be discussed.
EXAMPLES: Examples to be used in the workshop come from the presenter’s own research over the last 20+ years, involving homelessness and psychiatric care, using SPSS for the preparation of the data, supplemented by such programs SPSS’s Complex Samples Module, Excel, LISREL, and Maptitude. These examples involve: (i) direct standardization using ECA data, (ii) a structural equation approach to estimation of homeless populations, and most recently, (iii) two projects that estimates SMI rates and rates of homelessness using ‘regression synthetic estimation fitted using area-level covariates’, with data from the National Comorbidity Study and the U.S. Census.
PEDAGOGICAL APPROACH: The workshop will follow a standard format, using a PowerPoint presentation, supplemented by appropriate screen shots of statistical programs, research articles, and annotated syntax command files. This will be interspersed with questions and discussion.