Methods for handling missing data in clinical psychology studies are reviewed. Missing data
are defined, and a taxonomy of main approaches to analysis is presented, including …

University students studying science, technology, engineering, and mathematics (STEM)
tend to lose motivation, on average, over time. However, detailed understanding of when …

Background Identifying individuals with depressive symptomatology (DS) promptly and
effectively is of paramount importance for providing timely treatment. Machine learning …

Multiple imputation (MI) is one of the most popular methods for handling missing data in
psychological research. However, many imputation approaches are poorly equipped to …

The present study aimed to investigate the relative predictive power of teachers' beliefs
about cooperative learning, their participation in professional development courses on …

Missing data is a pervasive problem in many research contexts, including survey research.
Resulting analyses are dependent on data quality and which methods are used to deal with …

Financial stability is a key challenge for individuals living with bipolar disorder (BD).
Symptomatic periods in BD are associated with poor financial decision-making, contributing …

Cluster randomized trials (CRTs) are commonly used to evaluate the causal effects of
educational interventions, where the entire clusters (eg, schools) are randomly assigned to …

Ethnic–racial discrimination is a pernicious experience that affects discriminated
adolescents' healthy human development, but the spillover consequences of discrimination …

Background Childhood sexual abuse can increase both body weight and inflammation later
in life. Higher weight or faster changes in weight, as measured by changes in body mass …