GNBSTRAT: Stata module to estimate Generalized Negative Binomial with Endogenous Stratification

gnbstrat fits a maximum-likelihood generalized negative binomial with endogenous stratification regression model of depvar on indepvars, where depvar is a nonnegative count variable > 0. lnalpha is parameterized by the predictors entered within its parentheses. gnbstrat simultaneously accommodates three features of on-site samples dealing with count data: overdispersion relative to the Poisson; truncation at zero, and endogenous stratification due to oversampling of frequent users of the site. Endogenous stratification occurs when the likelihood of sampling observations is dependent on a choice made by the subject of study which is in itself the dependent variable. For example, in recreational demand analysis, if an on-site survey is conducted, one is more likely to interview subjects who visit the site more times per week and ask how many times they visit, hence the endogeneity. Also patients who visit the doctor more frequently are also more likely to be sampled if the survey is conducted at the clinic, etc.