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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.

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IMPACT FACTOR 2015: 0.667
5-year IMPACT FACTOR: 1.188

SCImago Journal Rank (SJR) 2015: 0.495
Source Normalized Impact per Paper (SNIP) 2015: 0.180
Impact per Publication (IPP) 2015: 0.319

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Online
ISSN
1557-4679
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In This Section

Sample Size Estimation for Repeated Measures Analysis in Randomized Clinical Trials with Missing Data

Kaifeng Lu
  • Merck & Co.
/ Xiaohui Luo
  • Merck & Co.
/ Pei-Yun Chen
  • Merck & Co.
Published Online: 2008-06-17 | DOI: https://doi.org/10.2202/1557-4679.1098

In designing longitudinal studies, researchers must determine the number of subjects to randomize based on the power to detect a clinically meaningful treatment difference and a proposed analysis plan. In this paper, we present formulas for sample size estimation and an assessment of statistical power for a two-treatment repeated measures design allowing for subject attrition. These formulas can be used for comparing two treatment groups across time in terms of linear contrasts. Subjects are assumed to drop out of the study at random so that the missing data do not alter the parameters of interest.

Keywords: completers analysis; missing at random; subject attrition

About the article

Published Online: 2008-06-17



Citation Information: The International Journal of Biostatistics, ISSN (Online) 1557-4679, DOI: https://doi.org/10.2202/1557-4679.1098. Export Citation

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