Brief Report: Polynomial Regression Mixture Modeling for Heterogeneous Effects of Informant Congruence

Using data from multiple informants has long been considered best practice in education. However, multiple informants often disagree on similar constructs, complicating decision-making. Polynomial regression and response-surface analysis (PRA) is often used to test the congruence effect between multiple informants on an outcome. However, PRA assumes the congruence effect on the outcome is homogeneous across individuals. To investigate unknown heterogeneity in the congruence effect, we introduce polynomial regression mixture modeling (PRMix). We demonstrate how PRMix enhances congruence research by allowing researchers to investigate individual differences in the congruence effect. The differential congruence effects between latent classes are illustrated with response-surface plots. We provide practical suggestions for using PRMix and discuss future research directions in methodology.

Automated summary

Using multiple informants in education has been considered best practice, but disagreement among informants complicates decision-making. To investigate heterogeneity in the congruence effect, this study introduces polynomial regression mixture modeling (PRMix). It demonstrates how PRMix enhances congruence research by allowing researchers to explore individual differences. Response-surface plots illustrate differential congruence effects between latent classes. Practical suggestions for using PRMix and future research directions are discussed.