Power Analysis and Sample Size Planning in ANCOVA Designs

Gwowen Shieh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The analysis of covariance (ANCOVA) has notably proven to be an effective tool in a broad range of scientific applications. Despite the well-documented literature about its principal uses and statistical properties, the corresponding power analysis for the general linear hypothesis tests of treatment differences remains a less discussed issue. The frequently recommended procedure is a direct application of the ANOVA formula in combination with a reduced degrees of freedom and a correlation-adjusted variance. This article aims to explicate the conceptual problems and practical limitations of the common method. An exact approach is proposed for power and sample size calculations in ANCOVA with random assignment and multinormal covariates. Both theoretical examination and numerical simulation are presented to justify the advantages of the suggested technique over the current formula. The improved solution is illustrated with an example regarding the comparative effectiveness of interventions. In order to facilitate the application of the described power and sample size calculations, accompanying computer programs are also presented.

Original languageEnglish
Pages (from-to)101-120
Number of pages20
JournalPsychometrika
Volume85
Issue number1
DOIs
StatePublished - 1 Apr 2020

Keywords

  • general linear hypothesis
  • omnibus test
  • power
  • sample size
  • CONFIDENCE-INTERVALS
  • MULTIPLE CORRELATION
  • STATISTICAL POWER
  • COVARIANCE
  • RESEARCHERS
  • TABLES
  • ANOVA

Fingerprint Dive into the research topics of 'Power Analysis and Sample Size Planning in ANCOVA Designs'. Together they form a unique fingerprint.

Cite this