Modeling Count Data using Stata
What you'll learn
- Understand count tables
- Calculate incidence-rate ratios
- Understand what count models are
- Identify when to use count models
- Poisson regression
- Negative binomial regression
- Truncated models
- Zero-inflated models
- Predict expected number of outcomes
- Apply count models using Stata
- Compare different models
- Visualise the results
Requirements
- Have a basic understanding of linear regression
- A slight understanding of logistic regression would help
Description
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.
Who this course is for:
- Beginner non-mathematical students seeking to become data scientists
Instructor
- 4.5 Instructor Rating
- 1,511 Reviews
- 17,155 Students
- 9 Courses
Najib Mozahem works as a researcher and as an assistant professor at university level, where he teaches Quantitative Analysis. He holds a Bachelor’s degree in Computer and Communication Engineering, completed his MBA with distinction, and completed his PhD in Organizational Theory where he won the best thesis prize for PhD. He has also received the teaching excellence award for the year 2016 – 2017. His research interests include quantitative modeling and the study of human behavior in organizations.