BackgroundLongitudinal data arise frequently in psychiatric investigations, and are most often analysed by multivariate analysis of variance (MANOVA) procedures. However, as routinely applied, the method is not satisfactory, particularly when the data are affected by subjects dropping-out of the study. More suitable methods are now available.MethodProblems with the MANOVA approach are discussed and the advantages of alternative procedures stressed.ResultsUsing MANOVA on complete cases to analyse unbalanced longitudinal data can be seriously misleading. More recently developed methods are far more suitable, but only if the missing values are non-informative.ConclusionsRoutine use of MANOVA for the analysis of longitudinal data, particularly when there is a substantial proportion of drop-outs, is ill advised. Statisticians have considerably enriched the available methodologies during the past decade, and psychiatric researchers dealing with such data should be aware of the advantages of the newer methods.