Effect of dropouts on sample size estimates for test on trends across repeated measurements.

Published

Journal Article

Sample size calculation is an important component at the design stage of clinical trials. We investigate the implications of dropouts for the sample size estimates in testing differences in the rates of changes produced by two treatments in a randomized parallel-groups repeated measurement design. Statistical models for calculating sample sizes for repeated measurement designs often fail to take into account the impact of dropouts correctly. In this article, we examine the impact of dropouts on sample size estimate and compare the power with the approach of Jung and Ahn [Jung, S. H., Ahn, C. (2003). Sample size estimation for GEE method for comparing slopes in repeated measurements data. Stat. Med. 22: 1305-1315] with that suggested by Patel and Rowe [Patel, H., Rowe, E. (1999). Sample size for comparing linear growth curves. J. Biopharm. Stat. 9:339-350] through a simulation study.

Full Text

Duke Authors

Cited Authors

  • Ahn, C; Jung, S-H

Published Date

  • 2005

Published In

Volume / Issue

  • 15 / 1

Start / End Page

  • 33 - 41

PubMed ID

  • 15702603

Pubmed Central ID

  • 15702603

International Standard Serial Number (ISSN)

  • 1054-3406

Digital Object Identifier (DOI)

  • 10.1081/bip-200040809

Language

  • eng

Conference Location

  • England