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Statistical Methods in Medical Research|January 12, 2011
Review of inverse probability weighting for dealing with missing dataShaun R Seaman, Ian R WhiteScandinavian Journal of Statistics, Theory and Applications|November 22, 2016
Linear Increments with Non-monotone Missing Data and Measurement ErrorShaun R Seaman, Daniel Farewell, Ian R WhiteBMC Medical Research Methodology|April 12, 2012
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methodsShaun R Seaman, Jonathan W Bartlett, Ian R WhiteStatistics in Medicine|July 18, 2020
A general method for elicitation, imputation, and sensitivity analysis for incomplete repeated binary dataDaniel Tompsett, Stephen Sutton, Shaun R Seaman, et al.Biometrics|November 5, 2011
Combining multiple imputation and inverse-probability weightingShaun R Seaman, Ian R White, Andrew J Copas, et al.Statistical Methods in Medical Research|February 15, 2014
Multiple imputation of covariates by fully conditional specification: Accommodating the substantive modelJonathan W Bartlett, Shaun R Seaman, Ian R White, et al.Statistics in Medicine|August 8, 2013
Multiple imputation for an incomplete covariate that is a ratioTim P Morris, Ian R White, Patrick Royston, et al.American Journal of Epidemiology|June 27, 2014
Correcting for optimistic prediction in small data setsGordon C S Smith, Shaun R Seaman, Angela M Wood, et al.BMC Medical Research Methodology|July 10, 2024
An evaluation of sample size requirements for developing risk prediction models with binary outcomesMenelaos Pavlou, Gareth Ambler, Chen Qu, et al.Statistical Methods in Medical Research|April 21, 2021
Estimation of required sample size for external validation of risk models for binary outcomesMenelaos Pavlou, Chen Qu, Rumana Z Omar, et al.Pageof 38