Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches.

James J. Jaccard, Choi K. Wan·1995·Psychological Bulletin

Cites (1)

Comparative fit indexes in structural models.
Bentler, P. M. · 1990 · Psychological Bulletin

Understanding Interaction Models: Improving Empirical Analyses
Brambor, Thomas, Clark, William Roberts, Golder, Matt · 2006 · Political Analysis
Testing moderator and mediator effects in counseling psychology research.
Frazier, Patricia A., Tix, Andrew P., Barron, Kenneth E. · 2004 · Journal of Counseling Psychology
A Tale of Three Perspectives: Examining Post Hoc Statistical Techniques for Detection and Correction of Common Method Variance
Richardson, Hettie A., Simmering, Marcia J., Sturman, Michael C. · 2009 · Organizational Research Methods
A Comparison of Bifactor and Second-Order Models of Quality of Life
Chen, Fang Fang, West, Stephen, Sousa, Karen · 2006 · Multivariate Behavioral Research
Marketing and technology resource complementarity: an analysis of their interaction effect in two environmental contexts
Song, Michael, Droge, Cornelia, Hanvanich, Sangphet, Calantone, Roger · 2005 · Strategic Management Journal

Cite CoChat for the checks on this page, and the paper for its own findings.

This page: CoChat. (2026). Citation check: Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches. https://app.cochat.ai/papers/10.1037//0033-2909.117.2.348
The paper: Jaccard, J. J., & Wan, C. K. (1995). Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches. Psychological Bulletin. https://doi.org/10.1037//0033-2909.117.2.348

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).