Misuse of analysis of covariance in aging research revisited.
Storandt and Hudson's treatment of the issue of which general linear model technique is preferable to use when age effects are confounded is misleading. Contrary to their position that hierarchical ANOVA or step-wise multiple regression is superior to ANCOVA, it is demonstrated, using hypothetical data, that identical amounts of variance can be explained by ANCOVA relative to hierarchical ANOVA and multiple regression. Multiple regression is recommended as the most appropriate technique for a variety of pragmatic reasons concerning calculation of significance tests, the distinction between gross and net effects, and the choice of the metric used in measurement.
D000328:Adult; D000368:Aged; D000375:Aging; D000704:Analysis of Variance; D004522:Educational Status; D006801:Humans; D007360:Intelligence; D008875:Middle Aged; D012044:Regression Analysis; D012107:Research Design; D013647:Task Performance and Analysis