Two common approaches to regression with missing covariates are complete-case analysis and ignorable likelihood methods. We review these approaches and propose a hybrid class, called subsample ignorable likelihood methods, which applies an ignorable likelihood method to the subsample of observations that are complete on one set of variables, but possibly incomplete on others. Conditions on… Continue reading Subsample ignorable likelihood for regression analysis with missing data