Multiple comparison of several linear regression models

Wei Liu, Mortaza Jamshidian, Ying Zhang

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Research on multiple comparison during the past 50 years or so has focused mainly on the comparison of several population means. Several years ago, Spurrier considered the multiple comparison of several simple linear regression lines. He constructed simultaneous confidence bands for all of the contrasts of the simple linear regression lines over the entire range (-∞, ∞) when the models have the same design matrices. This article extends Spurrier's work in several directions. First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals. Third, the types of comparison allowed can be very flexible, including pairwise, many-one, and successive. Two simulation methods are proposed for the calculation of critical constants. The methodologies are illustrated with examples.

Original languageEnglish (US)
Pages (from-to)395-403
Number of pages9
JournalJournal of the American Statistical Association
Volume99
Issue number466
DOIs
StatePublished - Jun 1 2004
Externally publishedYes

Keywords

  • Drug stability testing
  • Linear regression
  • Multiple comparisons
  • Simultaneous inference
  • Statistical simulation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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