Journal
STATISTICS IN MEDICINE
Volume 24, Issue 1, Pages 65-82Publisher
WILEY
DOI: 10.1002/sim.1923
Keywords
bivariate mixed model; repeated measurements; left-censoring; informative dropout; HIV infection
Categories
Funding
- Medical Research Council [MC_U122886351] Funding Source: Medline
Ask authors/readers for more resources
Several methodological issues occur in the context of the longitudinal study of HIV markers evolution. Three of them are of particular importance: (i) correlation between CD4+ T lymphocytes (CD4+) and plasma HIV RNA; (ii) left-censoring of HIV RNA due to a lower quantification limit; (iii) and potential informative dropout. We propose a likelihood inference for a parametric joint model including a bivariate linear mixed model for the two markers and a lognormal survival model for the time to drop out. We apply the model to data from patients starting antiretroviral treatment in the CASCADE collaboration where all of the three issues needed to be addressed. Copyright 2004 John Wiley Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available