The Limits of One-Size-Fits-All Patterns: A 5-Step Approach to Testing Homogeneity of Within-Person Correlations

Psychological research increasingly uses situated measures, requiring intensive longitudinal and within-person methods. Such data are typically examined with multilevel models clustering multiple measurement time points within individuals. The intercorrelation patterns obtained with such multilevel models rely on various homogeneity assumptions that should be, but rarely are, tested before using multilevel modeling and interpreting the results.This study proposes a five-step approach to systematically testing homogeneity assumptions in order to obtain more trustworthy estimates of associations among measures when examining clustered multilevel data.To provide an educational illustration of this five-step approach, 1,028 experience sampling method surveys from 37 students were collected over one semester in one university lecture. Twenty-one items measured motivational components and academic emotions. Multilevel analyses estimated an overall within-person and an overall between-person network of zero-order correlations among motivation and emotion facets. Idiographic within-person networks of the 37 participants revealed substantial heterogeneity in their within-person intercorrelation patterns. Heterogeneity was further indicated by one third of the within-person correlations being bi- or multimodally distributed across individuals. We conclude that heterogeneity in within-person patterns must be examined, otherwise, methods relying on homogeneity assumptions, including multilevel analyses, may fail to describe many if not all individuals’ idiographic correlation patterns. This is crucial for the trustworthiness of measurement and structure models, the generalizability of ESM research, and any research aiming for personalized diagnostics and interventions.