title: Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates.
abstract: Recently, multiple imputation has been proposed as a tool for individual patient data meta-analysis with sporadically missing observations, and it has been suggested that within-study imputation is usually preferable. However, such within study imputation cannot handle variables that are completely missing within studies. Further, if some of the contributing studies are relatively small, it may be appropriate to share information across studies when imputing. In this paper, we develop and evaluate a joint modelling approach to multiple imputation of individual patient data in meta-analysis, with an across-study probability distribution for the study specific covariance matrices. This retains the flexibility to allow for between-study heterogeneity when imputing while allowing (i) sharing information on the covariance matrix across studies when this is appropriate, and (ii) imputing variables that are wholly missing from studies. Simulation results show both equivalent performance to the within-study imputation approach where this is valid, and good results in more general, practically relevant, scenarios with studies of very different sizes, non-negligible between-study heterogeneity and wholly missing variables. We illustrate our approach using data from an individual patient data meta-analysis of hypertension trials. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
authors.affiliation: Department of Medical Statistics, London School of Hygiene & Tropical Medicine, Keppel St., London WC1E 7HT, U.K.
authors.forename: M
authors.initials: M
authors.lastname: Quartagno
authors.affiliation: Department of Medical Statistics, London School of Hygiene & Tropical Medicine, Keppel St., London WC1E 7HT, U.K.|MRC Clinical Trials Unit at UCL, Kingsway, London, U.K.
authors.forename: J R
authors.initials: JR
authors.lastname: Carpenter
mesh_terms: D002986:Clinical Trials as Topic; D000068598:Data Accuracy; D006801:Humans; D006973:Hypertension / Q000188:drug therapy; D015201:Meta-Analysis as Topic; D011336:Probability
keywords: IPD meta-analysis; heterogeneity; missing data