Longitudinal Data Analysis of Symptom Score Trajectories Using Linear Mixed Models in a Clinical Trial - Engel, C.; Meisner, C.; Wittorf, A.; Wölwer, W.; Wiedemann, G.; Ring, C.; Muche, R.; Klingberg, S. (International Journal of Statistics in Medical Research, 2013)
In clinical trials, longitudinal data are often analyzed using T-tests, anovas or ancovas instead of the more powerful linear mixed models. The purpose of this paper is to demonstrate how the more sophisticated linear mixed models according to the approach of Singer and Willett, which allows special insight into the behaviour of the data, can be used in clinical trials. Individual trajectories of PANNS-MNS Scores from a controlled clinical trial were used to demonstrate all the steps needed for an analysis of longitudinal data. The model is built step by step, model assumptions are checked, time-variant and time-invariant factors are included and the results are interpreted. The unique needs of a clinical trial, such as the calculation of effect sizes or of an appropriate sample size, are taken into account. Finally, a flow chart is presented that would serve as an instruction tool for the analysis of longitudinal data in clinical trials.