Abstract Purpose of Review In this review, we synthesize recent research that has reported
associations of a higher sense of purpose in life with reduced risk of develo** …

Statistical analyses are a crucial component of the biomedical research process and are
necessary to draw inferences from biomedical research data. The application of sound …

Background Missing data are unavoidable in epidemiological research, potentially leading
to bias and loss of precision. Multiple imputation (MI) is widely advocated as an …

Epidemiologic studies are frequently susceptible to missing information. Omitting
observations with missing variables remains a common strategy in epidemiologic studies …

Importance Three-generation family studies of depression have established added risk of
psychopathology for offspring with 2 previous generations affected with depression …

Handling missing values is a crucial step in preprocessing data in Machine Learning. Most
available algorithms for analyzing datasets in the feature selection process and …

Background: Population studies support the adverse associations of air pollution exposures
with child behavioral functioning and cognitive performance, but few studies have used …

Importance Early allograft dysfunction (EAD) following a liver transplant (LT) unequivocally
portends adverse graft and patient outcomes, but a widely accepted classification or grading …

Objective Non-response is unavoidable in longitudinal surveys. The consequences are
lower statistical power and the potential for bias. We implemented a systematic data-driven …

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for
clinicians, epidemiologists, and professional statisticians who need to make or evaluate a …