31 Oct 2013 11:00am

Handling incomplete multilevel data using multiple imputation and meta-analysis

Event Location
Ian White
MRC Biostatistics Unit, University of Cambridge

Multilevel data are often incomplete, and may be missing either at individual level or at cluster level. For example, in an observational meta-analysis of individual participant data exploring the association between carotid intima media thickness and subsequent risk of cardiovascular events, some relevant confounders were recorded in only 3 of 8 studies, and sporadic missingness also occurred. I will describe methods for tackling systematically missing covariates in this study by combining partly adjusted and fully adjusted analyses in a multivariate meta-analysis. I will also describe algorithms for multilevel multiple imputation which exploit two-stage meta-analysis methods.