Modeling Count Data Using Stata

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Poisson and Negative Binomial Regression Techniques

Last updated 2022-01-10 | 4.2

- Understand count tables
- Calculate incidence-rate ratios
- Understand what count models are

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

  • 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

Course content

7 sections • 29 lectures

Count tables 5 lectures

Introduction Preview 01:50

Count tables Preview 04:07

Risk Preview 02:05

Inceidence-rate ratio Preview 02:35

Two-by-three tables Preview 02:33

Poisson regression 6 lectures

Single independent variable Preview 16:44

Examples Preview 05:07

Binary variables Preview 06:12

Multiple independent variables Preview 06:31

Categorical variables Preview 08:21

Exposure Preview 08:26

Other count models 4 lectures

Negative binomial regression Preview 07:58

Truncated models Preview 04:02

Zero-inflated models Preview 17:31

Comparison of models Preview 07:39

Prediction 2 lectures

Predicting the number of events Preview 02:53

Predicting probabilities of certain counts Preview 02:44

Application: Fitting the model 6 lectures

Introduction to the dataset Preview 03:48

Continuous variables Preview 10:06

Binary variables Preview 03:55

Multivariate analysis Preview 02:09

Negative binomial regression Preview 02:34

Zero-inflated models Preview 10:12

Application: Model Comparison and Prediction 5 lectures

Comparing count models Preview 09:42

Model interpretation: predicted number of events Preview 08:11

Model interpretation: predicted probabilities of different outcomes Preview 04:53

Visualizing the model: predicted number of events Preview 04:45

Visualizing the model: predicted probabilities of different outcomes Preview 03:35

Conclusion 1 lectures

Conclusion Preview 01:43