
Explore count data modeling with Stata, learn why linear regression fails for nonnegative integer counts, and apply count model techniques using Stata's commands and visualization tools.
Calculate risk by dividing failures by total courses, then compare business and engineering students. Engineering shows higher risk (0.164) than business (0.144), with a ratio-based follow-up.
Explore exposure in count data and align incidence rate ratios with Poisson regression results by including an exposure variable, such as total courses or minutes played.
Explore zero-inflated models for count data with excess zeros, combining a binary inflation model with a count model to explain why zeros occur and predict counts.
Explore choosing count models like negative binomial and zero-inflated models, avoid truncated models, and predict the number of events, illustrating with GPA versus predicted event counts.
Visualize how the predicted number of events changes with GPA from 60 to 100 using margins and margins plot in Stata, via M change and M table commands.
Included in this course is an e-book and a set of slides. The course is divided into two parts. In the first part, students are introduced to the theory behind count models. The theory is explained in an intuitive way while keeping the math at a minimum. The course starts with an introduction to count tables, where students learn how to calculate the incidence-rate ratio. From there, the course moves on to Poisson regression where students learn how to include continuous, binary, and categorical variables. Students are then introduced to the concept of overdispersion and the use of negative binomial models to address this issue. Other count models such as truncated models and zero-inflated models are discussed.
In the second part of the course, students learn how to apply what they have learned using Stata. In this part, students will walk through a large project in order to fit Poisson, negative binomial, and zero-inflated models. The tools used to compare these models are also introduced.