Related Experiment Video
Updated: Oct 1, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Hierarchical-likelihood approach for mixed linear models with censored data
Il Do Ha1, Youngjo Lee, Jae-Kee Song
1Department of Statistics, Kyungsan University, Kyungsan, 712-240, South Korea. idha@kyungsan.ac.kr
Abstract:
Mixed linear models describe the dependence via random effects in multivariate normal survival data. Recently they have received considerable attention in the biomedical literature. They model the conditional survival times, whereas the alternative frailty model uses the conditional hazard rate. We develop an inferential method for the mixed linear model via Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). Simulation and a practical example are presented to illustrate the new method.
Related Concept Videos
Censoring Survival Data
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Assumptions of Survival Analysis