title: Multilevel mixed linear models for survival data.
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.
authors.affiliation: Faculty of Information Science, Daegu Haany University, Kyungsan, 712-240, South Korea. idha@dhu.ac.kr
authors.forename: Il Do
authors.initials: ID
authors.lastname: Ha
authors.forename: Youngjo
authors.initials: Y
authors.lastname: Lee
mesh_terms: D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007723:Korea; D015993:Life Tables; D016013:Likelihood Functions; D016014:Linear Models; D008297:Male; D012680:Sensitivity and Specificity; D016019:Survival Analysis