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Power Analysis and Sample Size Planning in ANCOVA Designs

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  • Gwowen Shieh

    (National Chiao Tung University)

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.

Suggested Citation

  • Gwowen Shieh, 2020. "Power Analysis and Sample Size Planning in ANCOVA Designs," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 101-120, March.
    • Handle: RePEc:spr:psycho:v:85:y:2020:i:1:d:10.1007_s11336-019-09692-3
    DOI: 10.1007/s11336-019-09692-3
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    References listed on IDEAS

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    1. Gwowen Shieh, 2006. "Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis," Psychometrika, Springer;The Psychometric Society, vol. 71(3), pages 529-540, September.
    2. 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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    Cited by:

    1. Roth, Lucas & Lowitzsch, Jens & Yildiz, Özgür, 2023. "Which (co-)ownership types in renewables are associated with the willingness to adopt energy-efficient technologies and energy-conscious behaviour? Data from German households," Energy Policy, Elsevier, vol. 180(C).

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