Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

@article{Preacher2006ComputationalTF,
  title={Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis},
  author={K. Preacher and P. Curran and D. Bauer},
  journal={Journal of Educational and Behavioral Statistics},
  year={2006},
  volume={31},
  pages={437 - 448}
}
  • K. Preacher, P. Curran, D. Bauer
  • Published 2006
  • Mathematics
  • Journal of Educational and Behavioral Statistics
  • 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… CONTINUE READING
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    References

    SHOWING 1-10 OF 22 REFERENCES
    Probing Interactions in Fixed and Multilevel Regression: Inferential and Graphical Techniques
    • 870
    • PDF
    Testing main effects and interactions in latent curve analysis.
    • 133
    • PDF
    Interpreting Hierarchical Linear and Hierarchical Generalized Linear Models With Slopes as Outcomes
    • 38
    Multiple Regression: Testing and Interpreting Interactions
    • 11,224
    • Highly Influential
    Moderator Variables in Prediction
    • 458
    Comparing nonparallel regression lines.
    • 227
    Testing and probing interactions
    • 2006