Longitudinal data with change-points

• Main Author: Zhou, Wei, 1968 Jan. 17-
• Format: Others
• Language: en
• Published: McGill University 2005
• Subjects: Statistics.
• Online Access: http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98532

Longitudinal data often consist of a set of covariates and repeated measurements of an outcome over time. In clinical and health studies, a main concern is often the time that a treatment takes into effect, which is referred to as the change-point in this thesis. Modeling and measuring impact of a change in longitudinal data has not been thoroughly explored in the statistical literature. Viewing longitudinal data from the perspective of change-point analysis, we have a data structure that statisticians sometimes refer to as a multi-path change-point problem. === In multipath change-point problems, it is often of interest to assess the impact of covariates on the change-point. We model the effect of covariates through hazard of the change using Cox's proportional odds model. We take a maximum quasi-likelihood (MqL) approach in estimation and statistical inference. To find the MqL estimators of the unknown parameters in our model, we have used a variant of simulated annealing. By the means of simulation we compare our model with a model suggested by Diggle et al. for analyzing a set of longitudinal observations on the body weights of 27 cows.