Misunderstanding analysis of covariance.
TL;DR: A nontechnical discussion is provided, emphasizing a substantive confound rarely articulated in textbooks and other general presentations, to complement the mathematical critiques already available.
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Abstract: Despite numerous technical treatments in many venues, analysis of covariance (ANCOVA) remains a widely misused approach to dealing with substantive group differences on potential covariates, particularly in psychopathology research. Published articles reach unfounded conclusions, and some statistics texts neglect the issue. The problem with ANCOVA in such cases is reviewed. In many cases, there is no means of achieving the superficially appealing goal of "correcting" or "controlling for" real group differences on a potential covariate. In hopes of curtailing misuse of ANCOVA and promoting appropriate use, a nontechnical discussion is provided, emphasizing a substantive confound rarely articulated in textbooks and other general presentations, to complement the mathematical critiques already available. Some alternatives are discussed for contexts in which ANCOVA is inappropriate or questionable. In research comparing groups of participants, classical experimental design (Campbell & Stanley, 1963) relies, whenever possible, on random assignment of participants to groups. Observed differences between such groups, prior to experimental treatments, are due to chance rather than being meaningfully related to the
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Misuses of Regression and ANCOVA in Educational Research
TL;DR: Education researchers sometimes use standardized regression coefficients (betas) as indices of predictor importance, even though this usage is unjustified for multiple regression.
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Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences.
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Lifetime and 12-Month Prevalence of DSM-III-R Psychiatric Disorders in the United States: Results From the National Comorbidity Survey
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