Multilevel mixed linear models for survival data.

Il Do Ha, Youngjo Lee
Author Information
  1. Il Do Ha: Faculty of Information Science, Daegu Haany University, Kyungsan, 712-240, South Korea. idha@dhu.ac.kr

Abstract

For the analysis of correlated survival data mixed linear models are useful alternatives to frailty models. By their use the survival times can be directly modelled, so that the interpretation of the fixed and random effects is straightforward. However, because of intractable integration involved with the use of marginal likelihood the class of models in use has been severely restricted. Such a difficulty can be avoided by using hierarchical-likelihood, which provides a statistically efficient and fast fitting algorithm for multilevel models. The proposed method is illustrated using the chronic granulomatous disease data. A simulation study is carried out to evaluate the performance.

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MeSH Term

Case-Control Studies
Data Interpretation, Statistical
Female
Humans
Korea
Life Tables
Likelihood Functions
Linear Models
Male
Sensitivity and Specificity
Survival Analysis

Word Cloud

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