Getting Started: COUNTREG Procedure

The COUNTREG procedure is similar in use to other regression model procedures in the SAS System. For example, the following statements are used to estimate a Poisson regression model:

   proc countreg data=one ;
      model y = x / dist=poisson ;
   run;

The response variable is numeric and has nonnegative integer values. To allow for variance greater than the mean, specify the dist=negbin option to fit the negative binomial model instead of the Poisson.

The following example illustrates the use of PROC COUNTREG. The data are taken from Long (1997). This study examines how factors such as gender (fem), marital status (mar), number of young children (kid5), prestige of the graduate program (phd), and number of articles published by a scientist’s mentor (ment) affect the number of articles (art) published by the scientist.

The first 10 observations are shown in Figure 10.1.

The following SAS statements estimate the Poisson regression model:

   /*-- Poisson Regression --*/
   proc countreg data=long97data;
      model art = fem mar kid5 phd ment / dist=poisson method=quanew;
   run;

The Model Fit Summary, shown in Figure 10.2, lists several details about the model. By default, the COUNTREG procedure uses the Newton-Raphson optimization technique. The maximum log-likelihood value is shown, as well as two information measures, Akaike’s information criterion (AIC) and Schwarz’s Bayesian information criterion (SBC), which can be used to compare competing Poisson models. Smaller values of these criteria indicate better models.