The nature of sensitivity in monotone missing not at random models. - Ivy Jansen; Niel Hens; Geert Molenberghs; Marc Aerts; Geert Verbeke; Michael G. Kenward (Comput. Stat. Data Anal., 2006)

An improved approximation to the precision of fixed effects from restricted maximum likelihood. - Michael G. Kenward; James H. Roger (Comput. Stat. Data Anal., 2009)

Semi-parametric marginal models for hierarchical data and their corresponding full models. - Geert Molenberghs; Michael G. Kenward (Comput. Stat. Data Anal., 2010)

MCMC-based estimation methods for continuous longitudinal data with non-random (non)-monotone missingness. - Cristina Sotto; Caroline Beunckens; Geert Molenberghs; Michael G. Kenward (Comput. Stat. Data Anal., 2011)

A method for increasing the robustness of multiple imputation. - Rhian M. Daniel; Michael G. Kenward (Comput. Stat. Data Anal., 2012)

Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations. - Donghwan Lee 001; Youngjo Lee 001; Myunghee Cho Paik; Michael G. Kenward (Comput. Stat. Data Anal., 2013)

Performance of parametric survival models under non-random interval censoring: A simulation study. - Nikos Pantazis; Michael G. Kenward; Giota Touloumi (Comput. Stat. Data Anal., 2013)

Fast, closed-form, and efficient estimators for hierarchical models with AR(1) covariance and unequal cluster sizes. - Lisa Hermans; Vahid Nassiri; Geert Molenberghs; Michael G. Kenward; Simon Vander Elst; Marc Aerts; Geert Verbeke (Commun. Stat. Simul. Comput., 2018)

Optimal weighted estimation versus Cochran-Mantel-Haenszel. - Lisa Hermans; Geert Molenberghs; Geert Verbeke; Michael G. Kenward; Pavlos Mamouris; Bert Vaes (Commun. Stat. Simul. Comput., 2022)