Abstract The polynomial combination (PC) method, proposed by Vink and Van Buuren, is a hot-deck multiple imputation method for models containing squared terms. yields unbiased regression estimates preserves the quadratic relationships in imputed data both MCAR MAR mechanisms. However, Buuren never studied coverage rate of PC method. This paper investigates nominal 95% confidence intervals impro...

This paper considers modelling spatially varying regression effects for multivariate mortality count outcomes. Alternative approaches to spatial regression heterogeneity are considered: the multivariate normal conditional autoregressive (MCAR) model is contrasted with a flexible set of priors based on the multiple membership approach. These include spatial factor priors and a nonparametric appr...

BACKGROUND Lung tumors are the leading cause of cancer deaths worldwide and paclitaxel has proven to be useful for patients with lung cancer, however, acquired resistance is a major problem. To overcome this problem, one promising option is the use of Constitutive Androstane Receptor (CAR) ligands in combination with chemotherapeutics against cancer cells. Therefore, we wish to elucidate the ef...

How do you handle missing data? Deletion of those subjects frequently leads to biased outcomes. Mean imputation assumes that non-responders are no different than responders, and can bias variances toward zero. Last observation carried forward methods, while still often used, can cause bias and even induce an apparent treatment effect. Multiple imputation is an improved method to deal with these...

A Hidden Markov Model with missing data in the outcome variable is considered. The initial and transition probabilities of chain emission probability HMM are allowed to depend on fully observed covariables. Tests for ignorable MCAR mechanisms proposed. These tests do not require grouping individuals by their pattern, making them easier apply practice. They based estimates conditional emitting a...