Joint analysis of correlated repeated measures and recurrent events processes in the presence of death, with application to a study on acquired immune deficiency syndrome

Lei Liu and Xuelin Huang

Journal of the Royal Statistical Society Series C, 2009, vol. 58, issue 1, 65-81

Abstract: Summary. In many longitudinal studies, we observe two correlated processes: a repeated measures process and a recurrent events process, both subject to a dependent terminal event. For example, in the ‘Terry Beirn community programs for clinical research on AIDS’ (CPCRA) study, higher CD4 cell counts are associated with lower risk of recurrent opportunistic diseases. They are also correlated with mortality, e.g. higher CD4 cell repeated measures and a lower rate of opportunistic disease imply better survival for patients infected with the human immunodeficiency virus. We propose a joint random‐effects model for the three correlated outcomes. The correlation is modelled by conditioning on shared random effects. Covariate effects can be taken into account in the model. Maximum likelihood estimation and inference are carried out through a Gaussian quadrature technique, assuming piecewise constant baseline hazards for recurrent events and death. The model can be fitted conveniently by Gaussian quadrature tools, e.g. SAS procedure NLMIXED. Simulation studies show that the estimation method yields satisfactory results. We apply this method to the CPCRA data.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2008.00641.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:58:y:2009:i:1:p:65-81

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().