We present motivation and new commands for modeling count data. While our focus is to present new commands for estimating count data, we also discuss generalized binomial regression and present the zero-inflated versions of each model. Copyright 2014 by StataCorp LP.

We describe specification and estimation of a multinomial treatment effects negative binomial regression model. A latent factor structure is used to accommodate selection into treatment, and a simulated likelihood method is used for estimation. We describe its implementation via the mtreatnb...

Studying behavior in economics, sociology, and statistics often involves fitting models in which the response variable depends on a dummy variable- also known as a regime-switch variable- or in which the response variable is observed only if a particular selection condition is met. In either...

We present motivation and new Stata commands for modeling count data. While the focus of this article is on modeling data with underdispersion, the new command for fitting generalized Poisson regression models is also suitable as an alternative to negative binomial regression for overdispersed data.

I present the rcpoisson command for right-censored count-data mod-els with a constant (Terza 1985, Economics Letters 18: 361–365) and variable censoring threshold (Caudill and Mixon 1995, Empirical Economics 20: 183–196). I show the effects of censoring on estimation results by comparing the...