ABSTRACT
Follow up studies are common in research where one like to see the changes over time on an individual due to corrective actions (interventions). Observations are repeatedly taken at specific time intervals on each subject of study and this data is multivariate in the time domain. Comparison of such data across study groups is a common problem in marketing research, longitudinal clinical research and behavioral studies. Popularly used in longitudinal clinical research with the follow-up studies the Repeated Measures (RM) ANOVA is the appropriate tool to do this.
This chapter illustrates the application of RM-ANOVA with real data software like SPSS and MedCalc. Statistical tools like Mauchley’s W statistic for test of sphericity and the Greenhouse-Geisser method are discussed in detail. An interesting application of RM ANOVA is the profile analysis used to compare the means of repeated measures of variables when observed on the same scale. Profiles that are flat, parallel or coincident are discussed with graphic illustrations. (158)
