Generalized linear models for the analysis of quality-improvement experiments

被引：70

作者：

Lee, Y

Nelder, JA

机构：

[1] Seoul Natl Univ, Dept Stat, Seoul 151742, South Korea

[2] Univ London Imperial Coll Sci Technol & Med, Dept Math, London SW7 2BZ, England

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 1998年 / 26卷 / 01期

关键词：

Taguchi method; quality improvement; generalized linear models; restricted maximum likelihood;

D O I：

10.2307/3315676

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：

Generalized linear models provide a useful tool for analyzing data from quality-improvement experiments. We discuss why analysis must be done for all the data, not just for summarizing quantities, and show by examples how residuals can be used for model checking. A restricted-maximum-likelihood-type adjustment for the dispersion analysis is developed.

引用

页码：95 / 105

页数：11

共 15 条

[1]

[Anonymous], 1991, Applied Stochastic Models and Data Analysis, DOI DOI 10.1002/ASM.3150070110

[2] TESTS OF HYPOTHESES IN OVERDISPERSED POISSON REGRESSION AND OTHER QUASI-LIKELIHOOD MODELS [J].