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Logistic Regression in R

In this session, Dr. Abioye led participants through how to conduct and interpret logistic regression for binary outcomes using real clinical examples. The class covers logistic models with continuous, binary, and categorical predictors, including how to choose reference groups and interpret odds ratios correctly. Learners are shown how to exponentiate model coefficients in R to obtain odds ratios and confidence intervals, and how to report effects meaningfully. The session also introduces multivariable logistic regression, adjustment for confounders, and model selection using AIC and likelihood ratio tests. Interaction terms are explored to assess effect modification and improve model interpretation.