Post-estimation commands for regression models for categorical and count outcomes

Jeremy Freese () and J. Scott Long ()
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Jeremy Freese: University of Wisconsin
J. Scott Long: University of Indiana

No 2.1, North American Stata Users' Group Meetings 2001 from Stata Users Group

Abstract: Although Stata has made estimating regression models for categorical and count outcomes virtually as fast and easy as estimating the familiar regression model for continuous outcomes, interpreting the results from the former is complicated by the nonlinear relationship between the independent variables and the dependent quantities of interest (i.e., predicted probabilities and predicted counts). As a consequence, the change in the predicted value associated with a unit change in the independent variable depends on the specific values of all of the independent variables. We have developed a series of tools that are intended to facilitate the effective use and interpretation of these models. Our command -listcoef- presents lists of different types of transformed coefficients from these models, and also provides a guide to their interpretation. A suite of commands, known collectively as -pr*-, computes predicted values and the discrete change for specified values of the independent variables. Our command -fitstat- computes a large number of goodness-of-fit statistics. Specifically for the multinomial logit model, the command -mlogtest- performs a number of commonly desired tests, and -mlogview- creates discrete change and/or odds ratio plots.

Date: 2001-01-15
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