✦ LIBER ✦

Use of Generalised Linear Mixed Models for the Analysis of Clustered Survival Data

✍ Scribed by K. K. W. Yau; C. A. McGilchrist

Publisher: John Wiley and Sons
Year: 1997
Tongue: English
Weight: 464 KB
Volume: 39
Category: Article
ISSN: 0323-3847
DOI: 10.1002/bimj.4710390102

No coin nor oath required. For personal study only.

✦ Synopsis

Data from a litter matched tumorigenesis experiment arc analysed using a gencralised h e a r mixed model (GLMM) approach to the analysis of clustered survival data in which there is a dependence of failure time observations withii the same litter. Maximum likelihood (ML.) and residual maximum likelihood (REML.) estimates of risk variable parameters, variance component parametem and the prediction of random effects are given. Estimation of treatment effect parameter (Carcinogen effect) has good agreement with previous analyses obtained in the literature though the dependence struchlre withii a litter is modelled in different ways. The variance component estimation provides the estimated dispersion of the random effects. The prediction of random effects. is ustful. for instance, in identifying high risk litters and individuals. The pment analysis illustrates its wider application to detecting increased risk of occurrence of disease in particular families of a study population.

📜 SIMILAR VOLUMES

Residuals analysis of the generalized li

Residuals analysis of the generalized linear models for longitudinal data

✍ Yue-Cune Chang 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 196 KB 👁 3 views

The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated

Variance components analysis for pedigre

Variance components analysis for pedigree-based censored survival data using generalized linear mixed models (GLMMs) and Gibbs sampling in BUGS

✍ Katrina J. Scurrah; Lyle J. Palmer; Paul R. Burton 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 123 KB 👁 2 views

Analysis of integrated circuit fault dat

Analysis of integrated circuit fault data using generalized linear models

✍ C. K. Hansen; P. Thyregod 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 344 KB 👁 2 views

Use of the Mann–Whitney U-test for clust

Use of the Mann–Whitney U-test for clustered data

✍ B. Rosner; D. Grove 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 233 KB 👁 2 views

The Mann}Whitney ;-test is ubiquitous in statistical practice for the comparison of measures of location for two samples where the assumption of normality is questionable. Frequently, one has replicate data for each individual in a group and would like to compare measures of central tendency between

Use of generalized linear mixed models i

Use of generalized linear mixed models in analyzing mutant frequency data from the transgenic mouse assay

✍ Karen Y. Fung; Xihong Lin; Daniel Krewski 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 69 KB 👁 2 views

The transgenic mouse assay is now widely used for ent sources of variation in the data can be evaluthe study of mutagenesis in diverse rodent tissues ated in nested factorial experiments and treatment and to test chemicals for genotoxic potential. This effects can be assessed simultaneously. It avoi

A general log-linear model for the analy

A general log-linear model for the analysis of band recovery data

✍ Michael C. Cooper; Douglas G. Bonett; Mohammed A. El-Saidi 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 174 KB 👁 2 views

Many current methods of analyzing band recovery data are described by the classic monograph Statistical Inference from Band Recovery Data ± A Handbook of Brownie et al. (1985). A log-linear model with restricted minimum modi®ed transformed chi-square estimation and Wald type testing are proposed. Th