a statistical procedure in which the variability of an outcome (typically a continuously measured variable) is accounted for by several different factors or predictors, each of which reflects a sampling of possible factor levels. The focus in a random-effects analysis of variance is on identifying differences in the mean values obtained on an outcome variable at the different levels of the predictors sampled. Compare fixed-effects analysis of variance.