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 present new commands for analyzing count-data regression models for truncated distributions. The trncregress command allows specification of a regression model for the mean of the truncated distribution through options. In addition to support for truncated Poisson and negative binomial,...

TWe present new Stata commands for estimating several regression models suitable for analyzing overdispersed count outcomes. The nbregp command nests the dispersion(constant) and dispersion(mean) versions of Stata’s nbreg command in a model for negative binomial(p) regression. The zignbreg...

We present new Stata commands for carrying out several regression commands suitable for binomial outcomes. The zib command extends Stata’s binreg command to allow zero inflation. The betabin command fits binomial regression models allowing for beta overdispersion, and the zibbin command fits a...

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed...

In the empirical analysis of information asymmetry in automobile insurance markets, prior research used a dichotomous measurement approach that induces excessive bundling in coverage measurements and sample selection biases. To improve on the conditional correlation method for testing...

Utilization of Antenatal Care (ANC) is very low in Nigeria. Self-reported patient satisfaction may be useful to identify provider- and facility-specific factors that can be improved to increase ANC satisfaction and utilization. Exit interview data collected from ANC users and facility assessment...