Introduction to longitudinal data analysis in psychiatric research

The onset, course, and management of mental health problems typically occur over relatively long periods of time, so a substantial proportion of psychiatric research – particularly the research that can provide clear answers about the complex interaction of biological, psychological, and social factors – requires multiple assessments of individuals and the environments in which they live over time. However, many psychiatric researchers use incorrect statistical methods to analyze this type of longitudinal data, a problem that can result in unrecognized bias in analytic results and, thus, incorrect conclusions. This paper provides an introduction to the topic of longitudinal data analysis. It discusses the different dataset structures used in the analysis of longitudinal data, the classification and management of missing data, and methods of adjusting for intra-individual correlation when developing multivariate regression models using longitudinal data.