A note on the sample size determination in two-period repeated measurements crossover design with application to clinical trials

L. Q. Yue, Paris Roach

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The two-period repeated measurements crossover design is often used in clinical trials. In this article we give a formula for sample size determination for testing treatment effect in two-period repeated measurements crossover design by taking an analysis of variance approach to the repeated measurements analysis. A balanced situation is considered: two treatment sequences that have the same number of patients, and the time points of measurements on each subject within each treatment period equal in number. The formula reveals the relationship between the required number of patients for each treatment sequence, the number of repeated measurements within each treatment period, the detectable treatment difference with respect to a primary response variable, and the power for testing the treatment difference. A clinical trial example is given to illustrate the use of the formula.

Original languageEnglish (US)
Pages (from-to)577-584
Number of pages8
JournalJournal of Biopharmaceutical Statistics
Volume8
Issue number4
StatePublished - 1998
Externally publishedYes

Fingerprint

Repeated Measurement Designs
Crossover Design
Sample Size Determination
Clinical Trials
Sample Size
Cross-Over Studies
Repeated Measurements
Therapeutics
Testing
Analysis of variance
Treatment Effects
Analysis of Variance

Keywords

  • Crossover design
  • Repeated measurements
  • Sample size determination
  • Treatment effects

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Pharmacology, Toxicology and Pharmaceutics(all)

Cite this

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AB - The two-period repeated measurements crossover design is often used in clinical trials. In this article we give a formula for sample size determination for testing treatment effect in two-period repeated measurements crossover design by taking an analysis of variance approach to the repeated measurements analysis. A balanced situation is considered: two treatment sequences that have the same number of patients, and the time points of measurements on each subject within each treatment period equal in number. The formula reveals the relationship between the required number of patients for each treatment sequence, the number of repeated measurements within each treatment period, the detectable treatment difference with respect to a primary response variable, and the power for testing the treatment difference. A clinical trial example is given to illustrate the use of the formula.

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