Probing Interactions in Multiple Linear
Regression, Latent Curve Analysis, and
Hierarchical Linear Modeling

Interactive calculation tools for establishing simple intercepts,
simple slopes, and regions of significance

Kristopher J. Preacher
University of Kansas

Patrick J. Curran and Daniel J. Bauer
University of North Carolina at Chapel Hill

HOW TO CITE THIS UTILITY: The paper describing this web utility may be cited in APA style in the following manner:

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437-448.

These web pages provide tools for probing significant 2-way or 3-way interaction effects in multiple linear regression (MLR), latent curve analysis (LCA), and hierarchical linear modeling (HLM). It is necessary first to obtain output from an appropriately conducted analysis investigating an interaction effect using other software. General discussions on how to conduct these analyses can be found in the references listed at the bottom of each page.

The primer on multiple linear regression contains a review of key concepts related to interaction effects in MLR.


All material on these pages not otherwise credited is ©2003 by Kristopher J. Preacher.
This page was first posted in September, 2003 and last updated on 8/10/06.
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