Multiple regression

Multiple regression: testing and interpreting interactions

by Aiken, Leona S

Type Book
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"In this comprehensive volume, Leona S. Aiken and Stephen G. West provide academicians and researchers with a clear set of prescriptions for estimating, testing, and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models or for those enrolled in courses on multivariate statistics."--Jacket

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Title Statements

  • Full title :Multiple regression : testing and interpreting interactions / Leona S. Aiken, Stephen G. West ; with contributions by Raymond R. Reno.

Summary

"In this comprehensive volume, Leona S. Aiken and Stephen G. West provide academicians and researchers with a clear set of prescriptions for estimating, testing, and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models or for those enrolled in courses on multivariate statistics."--Jacket

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Edition Statements

  • Publication Date:©1991

Publication Statements

  • Publisher(s):SAGE Publications
  • Place of Publication:Newbury Park, Calif
  • Language:eng
  • Publication Date:©1991

The Physical Object

  • Description:xi, 212 pages : : illustrations ; : 23 cm

Edition Identifiers

  • ISBN:0803936052, 9780803936058, 0761907122, 9780761907121
  • oclc:ocm23080434
  • LC Classification:QA278.2
  • Dewey Decimal:519.5/36

Table of Contents

Introduction -- Interactions between continuous predictors in multiple regression -- The effects of predictor scaling on coefficients of regression equations -- Testing and probing three-way interactions -- Structuring regression equations to reflect higher order relationships -- Model and effect testing with higher order terms -- Interactions between categorical and continuous variables -- Reliability and statistical power -- Conclusion: Some contrasts between ANOVA and MR in practice.

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