A cautionary note on the use of the Analysis of Covariance (ANCOVA) in classification designs with and without within-subject factors
Bruce A. Schneider; Meital Avivi-Reich; Mindaugas Mozuraitis · 2015 · Frontiers in Psychology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, it is not generally recognized that serious problems of interpretation can arise when the design contains comparisons of participants sampled from different populations (classification designs). Designs that include a comparison of younger and older adults, or a comparison of musicians and non-musicians are examples of classification designs. In such cases, estimates of differences among groups can
Abstract by Bruce A. Schneider; Meital Avivi-Reich; Mindaugas Mozuraitis, Frontiers in Psychology (2015) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3389/fpsyg.2015.00474