Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis
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Issue Date
2007-04-09Author
Preacher, Kristopher J.
Curran, Patrick J.
Bauer, Daniel J.
Type
Article
Is part of series
Journal of Educational and Behavioral Statistics
31, 437-448
Metadata
Show full item recordAbstract
Simple slopes, regions of significance, and confidence bands are commonly used
to evaluate interactions in multiple linear regression (MLR) models, and the use of
these techniques has recently been extended to multilevel or hierarchical linear
modeling (HLM) and latent curve analysis (LCA). However, conducting these
tests and plotting the conditional relations is often a tedious and error-prone task.
This article provides an overview of methods used to probe interaction effects and
describes a unified collection offreely available online resources that researchers
can use to obtain significance tests for simple slopes, compute regions of significance, and obtain confidence bands for simple slopes across the range of the moderator in the MLR, HLM, and LCA contexts. Plotting capabilities are also provided.
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