title: Introduction to longitudinal data analysis in psychiatric research.
abstract: 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.
authors.affiliation: DoD Deployment Health Clinical Center, Defense Center of Excellence for Psychological Health and Traumatic Brain Injury, Walter Reed National Military Medical Center, Bethesda, Maryland, United States ; Department of Psychiatry, F. Edward Hebert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States.
authors.forename: Xian
authors.initials: X
authors.lastname: Liu
keywords: Intra-individual correlation; longitudinal data; missing data; multivariate and univariate data structures; repeated measurements