Title
Multiple Comparison Of Several Linear Regression Models
Keywords
Drug stability testing; Linear regression; Multiple comparisons; Simultaneous inference; Statistical simulation
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.
Publication Date
6-1-2004
Publication Title
Journal of the American Statistical Association
Volume
99
Issue
466
Number of Pages
395-403
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1198/016214504000000395
Copyright Status
Unknown
Socpus ID
2942568478 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/2942568478
STARS Citation
Liu, Wei; Jamshidian, Mortaza; and Zhang, Ying, "Multiple Comparison Of Several Linear Regression Models" (2004). Scopus Export 2000s. 5179.
https://stars.library.ucf.edu/scopus2000/5179