Dealing With Binary Repeated Measures Data

Many longitudinal studies and randomized trials have binary outcomes that can repeat. For example, in a study evaluating the safety of a new drug, researchers might record whether a subject developed an adverse reaction at multiple time points during follow-up. These observations are correlated and thus require statistical tests that handle correlated data. Several different statistical models can be applied; this article reviews the advantages and disadvantages of each approach.

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