数学物理学报(英文版) ›› 2004, Vol. 24 ›› Issue (4): 559-568.

• 论文 • 上一篇    下一篇

TESTING FOR VARYING DISPERSION OF
LONGITUDINAL BINOMIAL DATA IN NONLINEAR
LOGISTIC MODELS WITH RANDOM EFFECTS

林金官,李博成   

  1. 1.Department of Mathematics, Southeast University, Nanjing 210096, China
    2.Department of Mathematics, Jiangsu Institute of Education, Nanjing 210013, China
  • 出版日期:2004-10-20 发布日期:2004-10-20
  • 基金资助:

    The project supported by NNSFC (19631040), NSSFC
    (04BTJ002) and the grant for post-doctor fellows in SEU.

TESTING FOR VARYING DISPERSION OF
LONGITUDINAL BINOMIAL DATA IN NONLINEAR
LOGISTIC MODELS WITH RANDOM EFFECTS

 LIN Jin-Guan, LI Bo-Cheng   

  • Online:2004-10-20 Published:2004-10-20
  • Supported by:

    The project supported by NNSFC (19631040), NSSFC
    (04BTJ002) and the grant for post-doctor fellows in SEU.

摘要:

In this paper, it is discussed that two tests for varying dispersion of binomial
data in the framework of nonlinear logistic models with random effects, which are widely
used in analyzing longitudinal binomial data. One is the individual test and power cal-
culation for varying dispersion through testing the randomness of cluster effects, which is
extensions of Dean(1992) and Commenges et al (1994). The second test is the composite
test for varying dispersion through simultaneously testing the randomness of cluster effects
and the equality of random-effect means. The score test statistics are constructed and ex-
pressed in simple, easy to use, matrix formulas. The authors illustrate their test methods
using the insecticide data (Giltinan, Capizzi & Malani (1988)).

Abstract:

In this paper, it is discussed that two tests for varying dispersion of binomial
data in the framework of nonlinear logistic models with random effects, which are widely
used in analyzing longitudinal binomial data. One is the individual test and power cal-
culation for varying dispersion through testing the randomness of cluster effects, which is
extensions of Dean(1992) and Commenges et al (1994). The second test is the composite
test for varying dispersion through simultaneously testing the randomness of cluster effects
and the equality of random-effect means. The score test statistics are constructed and ex-
pressed in simple, easy to use, matrix formulas. The authors illustrate their test methods
using the insecticide data (Giltinan, Capizzi & Malani (1988)).

Key words: Longitudinal binomial data;logistic regression;nonlinear models;power cal-
culation,
random effects;score test;varying dispersion

中图分类号: 

  • 62F25