The goal of multiple imputation is to provide valid inferences for statistical estimates from
incomplete data. To achieve that goal, imputed values should preserve the structure in the …

Missing data is a common occurrence in clinical research. Missing data occurs when the
value of the variables of interest are not measured or recorded for all subjects in the sample …

In preterm infants, poor postnatal growth is associated with adverse neurocognitive
outcomes; conversely, rapid postnatal growth is supposedly harmful for future development …

The R package mice imputes incomplete multivariate data by chained equations. The
software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R …

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …

This paper studies a non‐response problem in survival analysis where the occurrence of
missing data in the risk factor is related to mortality. In a study to determine the influence of …

The use of the Gibbs sampler with fully conditionally specified models, where the distribution
of each variable given the other variables is the starting point, has become a popular …

Since 1858, an increase of mean stature has been observed in the Netherlands, reflecting
the improving nutritional, hygienic, and health status of the population. In this study, stature …

Purpose–The purpose of the current study is to develop a generic and short questionnaire to
measure work performance at the individual level–the Individual Work Performance …

OBJECTIVES To compare the distribution of body mass index (BMI) in a national
representative study in The Netherlands in 1996–7 with that from a study in 1980 …