11. Johnson–Neyman and Picked-Points Solutions for Heterogeneous Regression

  1. Bradley E. Huitema

Published Online: 14 OCT 2011

DOI: 10.1002/9781118067475.ch11

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

How to Cite

Huitema, B. E. (2011) Johnson–Neyman and Picked-Points Solutions for Heterogeneous Regression, in The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118067475.ch11

Author Information

  1. Department of Psychology, Western Michigan University, Kalamazoo, Michigan, USA

Publication History

  1. Published Online: 14 OCT 2011
  2. Published Print: 14 OCT 2011

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780471748960

Online ISBN: 9781118067475

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Keywords:

  • assumption departures;
  • J–N and PPA methods;
  • multiple groups, one covariate

Summary

This chapter contains sections titled:

  • Introduction

  • J–N and PPA Methods for Two Groups, One Covariate

  • A Common Method That Should Be Avoided

  • Assumptions

  • Two Groups, Multiple Covariates

  • Multiple Groups, One Covariate

  • Any Number of Groups, Any Number of Covariates

  • Two-Factor Designs

  • Interpretation Problems

  • Multiple Dependent Variables

  • Nonlinear Johnson-Neyman Analysis

  • Correlated Samples

  • Robust Methods

  • Software

  • Summary