Module 5: Logistic Regression (Core Module)

Module 5: Logistic Regression (Core Module)

STATA playlist

Open the full YouTube playlist

Logistic regression is the central model in this course because it is the standard approach for binary outcomes. It estimates the probability that an event occurs while keeping predicted values within the 0 to 1 range, and it is commonly interpreted using odds ratios.

This module explains the model in applied terms: what the coefficients mean, why exponentiating them gives odds ratios, and how to distinguish a change in odds from a change in probability.

What students should understand

  • Use logistic regression when the dependent variable is coded 0/1.
  • logit reports coefficients in log-odds; logistic reports odds ratios directly.
  • Odds ratios are not the same as risk ratios.

STATA commands

logit outcome x1 x2 x3
logistic outcome x1 x2 x3
predict phat
margins

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