Longitudinal Structural Equation Modeling is a comprehensive resource that reviews
structural equation modeling (SEM) strategies for longitudinal data to help readers …

Aims To evaluate the effectiveness of two preventive interventions to reduce heavy drinking
in first‐and second‐year high school students. Design and setting Cluster randomized …

During the last few decades, and in order to increase product development efficiency,
simulations strategies have been developed to guide designers towards better solutions …

Multiple imputation under the assumption of multivariate normality has emerged as a
frequently used model-based approach in dealing with incomplete continuous data in recent …

Aims To examine the effects of a parent and student intervention offered separately and
simultaneously (PAS) on onset of weekly drinking via its putative mediators. Design A …

Sex hormone relationships for onset risks of rheumatoid arthritis (RA) were analyzed in a
nested case–control study, derived from a large community‐based prospective cohort. A self …

Most current implementations of multiple imputation (MI) assume that data are missing at
random (MAR), but this assumption is generally untestable. We performed analyses to test …

Situations in which multiple outcomes and predictors of different distributional types are
collected are becoming increasingly common in biopharmaceutical practice, and joint …

Ecological Momentary Assessment data present some new modeling opportunities.
Typically, there are sufficient data to explicitly model the within‐subject (WS) variance, and …

Multiple imputation by chained equations (MICE) is the most common method for imputing
missing data. In the MICE algorithm, imputation can be performed using a variety of …