A likelihood-based approach to defining statistical significance in proteomic analysis where missing data cannot be disregarded. - John Wood; Ian R. White; Paul Cutler (Signal Process., 2004)

Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables. - Ian R. White; Rhian M. Daniel; Patrick Royston (Comput. Stat. Data Anal., 2010)

rpsftm: An R Package for Rank Preserving Structural Failure Time Models. - Annabel Allison; Ian R. White; Simon Bond (R J., 2017)