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Can I read Estimating the Mean Hazard Ratio Parameters for Clustered Survival Data with Random Clusters on EtoBox?
Estimating the Mean Hazard Ratio Parameters for Clustered Survival Data with Random Clusters by Jianwen Cai; Haibo Zhou; C. E. Davis is a Mathematics article available to read on EtoBox.
What is Estimating the Mean Hazard Ratio Parameters for Clustered Survival Data with Random Clusters about?
We consider a latent variable hazard model for clustered survival data where clusters are a random sample from an underlying population. We allow interactions between the random cluster effect and covariates. We use a maximum pseudo-likelihood estimator to estimate the mean hazard ratio parameters. We propose a bootstrap sampling scheme to obtain an estimate of the variance of the proposed estimator. Application of this method in large multi-centre clinical trials allows one to assess the mean treatment effect, where we consider participating centres as a random sample from an underlying population. We evaluate properties of the proposed estimators via extensive simulation studies. A real data example from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention Trial illustrates the method.
Who reads Estimating the Mean Hazard Ratio Parameters for Clustered Survival Data with Random Clusters?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- Jianwen Cai; Haibo Zhou; C. E. Davis
- Publisher
- John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0277-6715)
- Published
- 1997
- Language
- EN
- Field
- Mathematics (Physical Sciences)