The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …

Descriptive analyses of socially important or theoretically interesting phenomena and trends
are a vital component of research in the behavioral, social, economic, and health sciences …

Many of the processes and outcomes of informal workplace learning remain almost
unnoticed by the learner, which makes it difficult to empirically investigate informal …

This chapter provides an overview of maximum likelihood estimation and multiple
imputation, two major missing data handling strategies with strong support from the …

In Bayesian statistics, the most widely used criteria of Bayesian model assessment and
comparison are Deviance Information Criterion (DIC) and Watanabe–Akaike Information …

A growing body of literature has focused on missing data methods that factorize the joint
distribution into a part representing the analysis model of interest and a part representing the …

For many years, rare earth elements (REEs) have been part of a wide range of applications
(from cell phones and batteries to electric vehicles and wind turbines) needed for daily life …

Partially clustered designs are widely used in psychological research, especially in
randomized controlled trials that examine the effectiveness of prevention or intervention …

High-dimensional complex survey data of general structures (eg, containing continuous,
binary, categorical, and ordinal variables), such as the US Department of Defense's Health …

We consider two-level models where a continuous response R and continuous covariates C
are assumed missing at random. Inferences based on maximum likelihood or Bayes are …