![]() ![]() The marginal means and errors for each level of the interaction should be presented in a mixed-effects ANOVA. ![]() ![]() You will be able to show evidence of how men change in number of hours watched from late August all the way until March of the next year and compare that level of change to how women change in number of hours watched along that same time frame. Therefore, you can assess how the number of hours watched changes across time AND between different groups. Gender is a "fixed" effect in that each participant is represented in one of the independent groups or levels of the "factor." Observations of number of hours of reality TV watched (let's say at the beginning of the college football season, then, at the beginning of the basketball season, and finally, at the end of March) is the "random" effect. The mixed-effects ANOVA compares how a continuous outcome changes across time (random effects) between independent groups or levels (fixed effects) of a categorical predictor variable.įor example, let's say researchers are interested in the change of number of hours of reality TV watched ( continuous outcome) between men and women (fixed effect) as the college football season leads into the college basketball season (random effect). ![]()
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