Critique of enhanced power claimed for Quasi-ANCOVA and Dual-Centered ANCOVA

Two related methods, Quasi-ANCOVA and Dual-Centered ANCOVA, have recently been suggested as a way to get greater power when analyzing data from a before and after study. Both methods use group-mean centering where the groups are the treatment and comparison groups. Group-mean centering creates a generated regressor problem. When the estimated standard errors are corrected for the generated regressor problem, there is no longer any gain in power. The corrected Quasi-ANCOVA estimates are identical to those from ANOVA and the corrected Dual-Centered ANCOVA estimates are identical to those from the differences model. These conclusions are derived analytically and also verified using a Monte Carlo simulation.

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Publication Details

Journal
PLoS ONE
Published
2025-01-22
DOI
https://doi.org/10.1371/journal.pone.0317860
Citations
2
Primary Topic
Statistical Methods and Inference
Type
article
Field-Weighted Citation Impact
5.26

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article

Critique of enhanced power claimed for Quasi-ANCOVA and Dual-Centered ANCOVA

Hua Lin, Robert E. Larzelere, B. Wade Brorsen
2 citations
PLoS ONE
Statistical Methods and Inference
5.26
article

Critique of enhanced power claimed for Quasi-ANCOVA and Dual-Centered ANCOVA

Hua Lin, Robert E. Larzelere, B. Wade Brorsen
article en
2 citations

Abstract

Two related methods, Quasi-ANCOVA and Dual-Centered ANCOVA, have recently been suggested as a way to get greater power when analyzing data from a before and after study. Both methods use group-mean centering where the groups are the treatment and comparison groups. Group-mean centering creates a generated regressor problem. When the estimated standard errors are corrected for the generated regressor problem, there is no longer any gain in power. The corrected Quasi-ANCOVA estimates are identical to those from ANOVA and the corrected Dual-Centered ANCOVA estimates are identical to those from the differences model. These conclusions are derived analytically and also verified using a Monte Carlo simulation.

PLoS ONEVol. 20(1)
Oklahoma State University (US)
U.S. Department of Agriculture, National Institute of Food and Agriculture, Oklahoma Agricultural Experiment Station, National Institute of Child Health and Human Development
Openalex Percentile: Top 7%
Statistical Methods and Inference
5.26
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Critique of enhanced power claimed for Quasi-ANCOVA and Dual-Centered ANCOVA — Hua Lin, Robert E. Larzelere, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS