any statistical procedure or experimental design that involves random effects. For example, a researcher wishing to investigate the effects of temperature on the frequency of aggressive behavior could not easily examine each temperature value and so instead examines a random sample of such values and their effects. Although random-effects models tend to be less powerful than fixed-effects models, they enable generalization to levels of the independent variable not actually employed in the study. Also called random model. Compare mixed-effects model.