Sample sizes required to detect interactions between two binary fixed-effects in a mixed-effects linear regression model

Andrew C. Leon, Moonseong Heo

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

Mixed-effects linear regression models have become more widely used for analysis of repeatedly measured outcomes in clinical trials over the past decade. There are formulae and tables for estimating sample sizes required to detect the main effects of treatment and the treatment by time interactions for those models. A formula is proposed to estimate the sample size required to detect an interaction between two binary variables in a factorial design with repeated measures of a continuous outcome. The formula is based, in part, on the fact that the variance of an interaction is fourfold that of the main effect. A simulation study examines the statistical power associated with the resulting sample sizes in a mixed-effects linear regression model with a random intercept. The simulation varies the magnitude (Δ) of the standardized main effects and interactions, the intraclass correlation coefficient (ρ), and the number (k) of repeated measures within-subject. The results of the simulation study verify that the sample size required to detect a 2×2 interaction in a mixed-effects linear regression model is fourfold that to detect a main effect of the same magnitude.

Original languageEnglish (US)
Pages (from-to)603-608
Number of pages6
JournalComputational Statistics and Data Analysis
Volume53
Issue number3
DOIs
StatePublished - Jan 15 2009
Externally publishedYes

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Mixed Effects
Fixed Effects
Linear Regression Model
Linear regression
Main Effect
Sample Size
Binary
Interaction
Repeated Measures
Simulation Study
Intraclass Correlation Coefficient
Statistical Power
Binary Variables
Factorial Design
Intercept
Clinical Trials
Tables
Vary
Verify
Estimate

ASJC Scopus subject areas

  • Computational Mathematics
  • Computational Theory and Mathematics
  • Statistics and Probability
  • Applied Mathematics

Cite this

Sample sizes required to detect interactions between two binary fixed-effects in a mixed-effects linear regression model. / Leon, Andrew C.; Heo, Moonseong.

In: Computational Statistics and Data Analysis, Vol. 53, No. 3, 15.01.2009, p. 603-608.

Research output: Contribution to journalArticle

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