title: Dropout in crossover and longitudinal studies: is complete case so bad?
abstract: We discuss inference for longitudinal clinical trials subject to possibly informative dropout. A selection of available methods is reviewed for the simple case of trials with two timepoints. Using data from two such clinical trials, each with two treatments, we demonstrate that different analysis methods can at times lead to quite different conclusions from the same data. We investigate properties of complete-case estimators for the type of trials considered, with emphasis on interpretation and meaning of parameters. We contrast longitudinal and crossover designs and argue that for crossover studies there are often good reasons to prefer a complete case analysis. More generally, we suggest that there is merit in an approach in which no untestable assumptions are made. Such an approach would combine a dropout analysis, an analysis of complete-case data only, and a careful statement of justified conclusions.
authors.affiliation: 1Mathematics & Statistics, Newcastle University, UK.
authors.forename: John N S
authors.initials: JN
authors.lastname: Matthews
authors.forename: Robin
authors.initials: R
authors.lastname: Henderson
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Farewell
authors.forename: Weang-Kee
authors.initials: WK
authors.lastname: Ho
authors.forename: Lauren R
authors.initials: LR
authors.lastname: Rodgers
mesh_terms: D002986:Clinical Trials as Topic; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D010352:Patient Dropouts