Sample-size calculation for a log-transformed outcome measure.
The outcome measure of interest in clinical trials sometimes requires transformation to the logarithmic scale for analysis. This paper examines sample-size calculation for both independent groups and matched-pairs trials for log-transformed outcomes. For both types of trial, we demonstrate how the calculation can be formulated in terms of a relative treatment effect and a statement of relative variability, both specified on the original scale of measurement. For a comparison of two independent groups, the relative treatment effect is the ratio of group geometric means (or alternatively, group arithmetic means) and the coefficient of variation is used as a summary of relative variability. For a matched-pairs comparison, the appropriate relative treatment effect is the geometric mean of the within-pair ratios, and relative variability can be specified as an upper bound on within-pair ratios under a null hypothesis of the relative effect being equal to 1 (i.e., no difference). We discuss the clinical study that motivated this work and demonstrate the application of the sample-size calculation to this study.
Wolfe
R
R
Clinical Epidemiology and Biostatistics Unit, Royal Children's Hospital Research Institute, Parkville, Australia.
Carlin
J B
JB
D000465:Algorithms; D000779:Anesthetics, Local / Q000008:administration & dosage; D016022:Case-Control Studies; D002648:Child; D006801:Humans; D007252:Influenza Vaccines / Q000008:administration & dosage; D007279:Injections, Subcutaneous / Q000009:adverse effects; D016014:Linear Models; D009824:Ointments; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010146:Pain / Q000517:prevention & control; D010919:Placebos; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D018401:Sample Size; D013748:Tetracaine / Q000008:administration & dosage; D016896:Treatment Outcome; D014611:Vaccination
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