Andrew J Vickers1. 1. Integrative Medicine Service, Biostatistics Service, Memorial Sloan Kettering Cancer Center, Howard 1312a, 1275 York Avenue, NY 10021, USA. vickersa@mskcc.org
Abstract
OBJECTIVE: The objective of this study was to determine whether standard deviations (SDs) used in sample size calculations are smaller than those found in the resulting study sample, thereby leading to underpowered studies. METHOD: The predicted SD used in the sample size calculation and the actual SD of the study sample were recorded for randomized trials recently published in one of four major journals. RESULTS: Sample SD was greater than predicted SD for 80% of endpoints. About one quarter of trials required five times as many patients as specified in the sample size calculation. CONCLUSION: Trials reporting sample size calculations for continuous endpoints published in the most reputable medical journals are often underpowered. There seems to be insufficient understanding that the SD of a sample of patients is a random variable, associated with imprecision, that cannot easily be extrapolated from one population to another.
OBJECTIVE: The objective of this study was to determine whether standard deviations (SDs) used in sample size calculations are smaller than those found in the resulting study sample, thereby leading to underpowered studies. METHOD: The predicted SD used in the sample size calculation and the actual SD of the study sample were recorded for randomized trials recently published in one of four major journals. RESULTS: Sample SD was greater than predicted SD for 80% of endpoints. About one quarter of trials required five times as many patients as specified in the sample size calculation. CONCLUSION: Trials reporting sample size calculations for continuous endpoints published in the most reputable medical journals are often underpowered. There seems to be insufficient understanding that the SD of a sample of patients is a random variable, associated with imprecision, that cannot easily be extrapolated from one population to another.
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