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A power approximation for the Kenward and Roger Wald test in the linear mixed model

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  • Sarah M Kreidler
  • Brandy M Ringham
  • Keith E Muller
  • Deborah H Glueck

Abstract

We derive a noncentral F power approximation for the Kenward and Roger test. We use a method of moments approach to form an approximate distribution for the Kenward and Roger scaled Wald statistic, under the alternative. The result depends on the approximate moments of the unscaled Wald statistic. Via Monte Carlo simulation, we demonstrate that the new power approximation is accurate for cluster randomized trials and longitudinal study designs. The method retains accuracy for small sample sizes, even in the presence of missing data. We illustrate the method with a power calculation for an unbalanced group-randomized trial in oral cancer prevention.

Suggested Citation

  • Sarah M Kreidler & Brandy M Ringham & Keith E Muller & Deborah H Glueck, 2021. "A power approximation for the Kenward and Roger Wald test in the linear mixed model," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-19, July.
    • Handle: RePEc:plo:pone00:0254811
    DOI: 10.1371/journal.pone.0254811
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    References listed on IDEAS

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    1. Gwowen Shieh, 2007. "A Unified Approach to Power Calculation and Sample Size Determination for Random Regression Models," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 347-360, September.
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