Supervised machine learning (ML) is becoming an influential analytical method in
psychology and other social sciences. However, theoretical ML concepts and predictive …

This scoping review aimed to synthesise methodological steps taken by researchers in the
development of formal, dynamical systems models of health psychology theories. We …

Theories are the vehicle of cumulative knowledge acquisition. At this time, however, many
(developmental) psychological theories are insufficiently precise to derive testable …

In the real world of international business, machine learning (ML) is well established as an
essential element in many operations, from finance and logistics to marketing and strategy …

Researchers have focused extensively on understanding the factors influencing students'
academic achievement over time. However, existing longitudinal studies have often …

Random forests are a nonparametric machine learning method, which is currently gaining
popularity in the behavioral sciences. Despite random forests' potential advantages over …

Prior research on the relations between the five-factor model (FFM) of personality traits and
job performance has suggested mixed findings: Some studies pointed to linear relations …

Social interactions are essential for well-being. Therefore, researchers increasingly attempt
to capture an individual's social context to predict well-being, including mood. Different tools …

Abstract Machine learning explainability techniques have been proposed as a means for
psychologists to “explain” or interrogate a model in order to gain an understanding of a …

Gradient tree boosting is a powerful machine learning technique that has shown good
performance in predicting a variety of outcomes. However, when applied to hierarchical (eg …