Handling incomplete multilevel data using multiple imputation and meta-analysis

Thursday, 31 October 2013
9:30am - 10:30am
Ella Latham Auditorium, Royal Childrens Hospital
Flemington Road
Parkville 3052

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.


Dr Ian White

MRC Biostatistics Unit
University Of Cambridge

Dr Ian White is a Programme Leader at the MRC (Medical Research Council) Biostatistics Unit at the University of Cambridge, his main biostatistics research areas are statistical methods for handling missing data and heterogeneity in meta-analyses.

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