Improving small-sample inference in group randomized trials with binary outcomes

Group Randomized Trials (GRTs) randomize groups of people to treatment or control arms instead of individually randomizing subjects. When each subject has a binary outcome, over‐dispersed binomial data may result, quantified as an intra‐cluster correlation (ICC). Typically, GRTs have a small number,...

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Veröffentlicht in:	Statistics in medicine 2011-02, Vol.30 (3), p.201-210
Hauptverfasser:	Westgate, Philip M., Braun, Thomas M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bias bias correction Clinical outcomes Cluster Analysis Computer Simulation correlated data Humans Logistic Models Medical research Medical statistics Medical treatment Models, Statistical overdispersion Probability pseudo-Wald tests quasi-likelihood Randomized Controlled Trials as Topic - methods Sample Size Simulation Statistical Distributions Treatment Outcome
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