ABSTRACT
In a typical longitudinal study, multiple observations were taken during the course of the study. Analysis of response profile data helps to better understand how the interventions work during the whole course of experiments than data analysis only focuses on the last observation. In this chapter, we provide a case study of clinical trial data examining the whole response profile of each patient and trying to investigate the potential relationship of the responses with clinical factors and patient's background information. We demonstrate the treatment effects longitudinally by graphical methods, we also estimate the probability of changing disease status during the study, and the similarity of response profiles so that patients can be segmented into subgroups or clusters, and further investigate the differences between the clusters. The same methodologies and procedures can be applied to other areas of research, including market research, epidemiology, etc., with longitudinal data for behavior tracking or long-term trend.
