Key results of interaction models with centering

David Afshartous, Richard A Preston

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

We consider the effect on estimation of simultaneous variable centering and interaction effects in linear regression. We technically define, review, and amplify many of the statistical issues for interaction models with centering in order to create a useful and compact reference for teachers, students, and applied researchers. In addition, we investigate a sequence of models that have an interaction effect and/or variable centering and derive expressions for the change in the regression coefficients between models from both an intuitive and mathematical perspective. We demonstrate how these topics may be employed to motivate discussion of other important areas, e.g., misspecification bias, multicollinearity, design of experiments, and regression surfaces. This paper presents a number of results also given elsewhere but in a form that gives a unified view of the topic. The examples cited are from the area of medical statistics.

Original languageEnglish
JournalJournal of Statistics Education
Volume19
Issue number3
StatePublished - Nov 1 2011

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Interaction Effects
regression
interaction
Interaction
Multicollinearity
Misspecification
Design of Experiments
Regression Coefficient
Linear regression
student teacher
Intuitive
Regression
statistics
Model
Statistics
experiment
trend
Demonstrate
Interaction effects
Review

Keywords

  • Beta coefficients
  • Introductory statistics
  • Medical statistics
  • Misspecification bias
  • Multicollinearity
  • Multiple regression

ASJC Scopus subject areas

  • Education
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Key results of interaction models with centering. / Afshartous, David; Preston, Richard A.

In: Journal of Statistics Education, Vol. 19, No. 3, 01.11.2011.

Research output: Contribution to journalArticle

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