Summary

This training module provides an overview on binary response models. We will look at the Linear Probability Model (LPM) and  some of the challenges associated with its use. Then we will look at the two more common alternatives; the Probit and Logit Models.

Objectives

1. Providing a review of why and when we use binary response models.
2. Discussing the main binary response models (LPM, Probit and Logit) and when we might use one over the other.
3. Understanding how to interpret results from binary response models with continuous and binary explanatory variables.
4. Understanding how to implement analysis using binary response models in STATA.
5. Providing guiding steps on evaluating binary response models.

Contributors

Saweda Liverpool-Tasie (MSU), Nicole Mason-Wardell (MSU), Paul Samboko (MSU)

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