In recent years, psychological research has increasingly utilized novel (often digital) data sources. Sensing data, such as those collected from smartphones, enable researchers to monitor human behavior across diverse, ecologically valid contexts and extended periods with relative ease. These rich datasets offer great potential for predicting psychological traits, such as personality facets,...
Psychology is increasingly interested in the prediction of psychological constructs via machine learning (ML) models, for example, predicting a person’s personality or intelligence. To measure these psychological constructs, psychologists often draw on questionnaire data. In supervised ML, these measurements are then used as target variables (i.e., the “ground truth”) for model training....
With the advent of machine learning tools and large language models (LLMs), the collection of measurements related to social science constructs (e.g., personality traits, political attitudes, human values) has become easier, faster and more affordable. These measurements are subsequently used for modelling of societal and group processes that social scientists typically engage in, where...
Despite the popularity of structural equation modeling (SEM), investigating the fit of SEM models is still challenging—especially, if the global model fit evaluation implies non-negligible misfit, and researchers need to further investigate the type and severity of the misspecification in their model. Being overwhelmed by poorly fitting models, researchers sometimes strain the interpretation...
