Author:

Keywords:

Antifungal Agents, Belgium, Controlled Clinical Trials, Data Interpretation, Statistical, Foot Dermatoses, Humans, Linear Models, Logistic Models, Longitudinal Studies, Onychomycosis, Research Design, Treatment Outcome, Science & Technology, Life Sciences & Biomedicine, Physical Sciences, Mathematical & Computational Biology, Public, Environmental & Occupational Health, Medical Informatics, Medicine, Research & Experimental, Statistics & Probability, Research & Experimental Medicine, Mathematics, generalized estimating equations, generalized linear mixed models, interim analyses, logistic regression, repeated measurements, RANDOM-EFFECTS MODELS, CLINICAL-TRIALS, DESIGN, INFORMATION, ONYCHOMYCOSIS, BOUNDARIES, TESTS, Controlled Clinical Trials as Topic, 0104 Statistics, 1117 Public Health and Health Services, 4202 Epidemiology, 4905 Statistics

Abstract:

Interim analyses are conducted to allow for early termination of the trial, for ethical as well as economical reasons. Here we consider interim analyses in repeated measurements studies where the measurements are binary. Two methods for analysing this kind of data are compared according to their operating characteristics. A subject-specific approach based on the logistic random-effects model is compared with the population-averaged approach based on the generalized estimating equations. The comparison is illustrated with simulations using a randomized clinical trial for toenail fungal infection.