Repeated Measures ANOVA

Abstract In marketing research, one of the sources of variability in the observed measures is the respondents themselves. The respondents come from different backgrounds and have unique individual characteristics, and thus can perceive a study differently. Since this sample level variability reduces the effectiveness of the study, it is very important to separate it from the treatment effects and the experimental errors. Unfortunately, these differences among subjects are uncontrolled and are treated as errors in a between‐subject design. Therefore, we use a within‐subject design where the respondents are exposed to more than one treatment condition and hence repeated measures are obtained. Such repeated measures are also necessary in longitudinal studies where respondents are measured at different time periods and in cases where it is difficult to recruit respondents. Traditional analysis of variance (ANOVA) is not adequate to analyze this type of data as it is unable to control the correlation among the repeated measures. Therefore, a different analysis called repeated measures ANOVA is used. Repeated measures ANOVA is also considered as an extension of a paired‐sample t ‐test to a case of more than two related samples.