Multivariate Data Exploration with Stata: Evaluation and Wish List

Stata is a general purpose statistical package with especially strong data manipulation and regression modeling capabilities. It appears to be especially strong in statistical techniques used by econometricians and biostatisticians. As psychologists, among others, adopt it, certain relative weaknesses in the existing set of implemented procedures become apparent. In particular, multidimensional exploratory data analyses are a set of data analytic procedures -- including principal components and factor analysis, correspondence analysis, optimal scaling, and multidimensional scaling, -- commonly used to explore the structure of data sets and derive variables (e.g., principal components or factors) that summarize the data in a small number of variables. While Stata, as delivered or through user add-ons, has many of the basic capabilities in these areas, many are implemented in a fairly rudimentary fashion and others are implemented in the Stata executable, without sufficient hooks for users to be able to expand them. This talk will discuss some of these procedures and will evaluate Stata capabilities in these areas. It is hoped that it will help stimulate Stata Corp or the user community to expand Stata capabilities in these areas.