Multiple comparison of several linear regression models

被引:62
|
作者
Liu, W [1 ]
Jamshidian, M
Zhang, Y
机构
[1] Univ Southampton, Inst Stat Sci, Southampton SO17 1BJ, Hants, England
[2] Univ Southampton, Sch Math, Southampton SO17 1BJ, Hants, England
[3] Calif State Univ Fullerton, Dept Math, Fullerton, CA 92834 USA
[4] Univ Cent Florida, Dept Stat & Actuarial Sci, Orlando, FL 32816 USA
关键词
drug stability testing; linear regression; multiple comparisons; simultaneous inference; statistical simulation;
D O I
10.1198/016214504000000395
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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 (-infinity, infinity) 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.
引用
收藏
页码:395 / 403
页数:9
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