Hypothesis testing in clinical trials.
In designing and analyzing any clinical trial, two issues related to patient heterogeneity must be considered: (1) the effect of chance and (2) the effect of bias. These issues are addressed by enrolling adequate numbers of patients in the study and using randomization for treatment assignment. An "intention-to-treat" analysis of outcome data includes all individuals randomized and counted in the group to which they are randomized. There is an increased risk of spurious results with a greater number of subgroup analyses, particularly when these analyses are data derived. Factorial designs are sometimes appropriate and can lead to efficiencies by addressing more than one comparison of interventions in a single trial.
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Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
D002986:Clinical Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D005163:Factor Analysis, Statistical; D006801:Humans; D009042:Motivation; D010361:Patients / Q000145:classification; D011897:Random Allocation; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data; D012107:Research Design; D012494:Sampling Studies; D016896:Treatment Outcome