2005/03/01 by Yu‐Kang Tu, Y.-K. Tu, A. Blance +4 · 4 citations
Decision Sciences · Mathematics · Medicine · #Analysis of covariance #Equivalence (formal languages) #Internal medicine #Mathematics #Medicine #Meta-analysis and systematic reviews #Multivariate statistics #Outcome (game theory) #Randomized controlled trial #Sample size determination #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials #Statistical analysis #Statistical hypothesis testing #Statistical power #Statistics #Univariate
paper · doi:10.1177/154405910508400315
openalex publication_date 2005/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/27
Randomized controlled trials (RCTs) are widely recommended as the most useful study design to generate reliable evidence and guidance to daily practices in medicine and dentistry. However, it is not well-known in dental research that different statistical methods of data analysis can yield substantial differences in study power. In this study, computer simulations are used to explore how using different univariate and multivariate statistical methods of analyzing change in continuous outcome variables affects study power, and the sample size required for RCTs. Results show that, in general, analysis of covariance (ANCOVA) yields greater power than other statistical methods in testing the superiority of one treatment over another, or in testing the equivalence between two treatments. Therefore, ANCOVA should be used in preference to change score or percentage change score to reduce type II error rates.