James Carpenter (London School of Hygiene and Tropical Medicine)
- what is multiple imputation, how is it done, and what can it achieve?
Jonathan Bartlett (London School of Hygiene and Tropical Medicine)
Accommodating the model of interest within the fully conditional multiple imputation framework (slides coming soon)
Multiple imputation of covariates allowing for:
- models of interest which include non-linear terms or interactions
- non-linear models of interest, such as Poisson regression or Cox proportional hazards models
Rachael Hughes (University of Bristol)
Comparison of imputation variance estimators (slides coming soon)
- Potential pitfalls of multiple imputation when the imputation and analysis models are misspecified and/or incompatible.
- Different approaches to imputation inference in different scenarios of misspecification
Ofer Harel (University of Connecticut)
- strategies for analysis with two types of missing values
Shaun Seaman (MRC Biostatistics Unit, Cambridge)
- Why combine inverse probability weighting with multiple imputation to handle missing data?
- Using multiple imputation in studies with sampling weights