Joint modelling of bivariate longitudinal data with informative dropout and left-censoring, with application to the evolution of CD4+ cell count and HIV RNA viral load in response to treatment of HIV infection-Reference-Cited by-同舟云学术

Joint modelling of bivariate longitudinal data with informative dropout and left-censoring, with application to the evolution of CD4+ cell count and HIV RNA viral load in response to treatment of HIV infection

Published:2004 Issue:1 Volume:24 Page:65-82
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Thiébaut Rodolphe,Jacqmin-Gadda Hélène,Babiker Abdel,Commenges Daniel,

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference31 articles.

1. Survival after introduction of HAART in people with known duration of HIV-1 infection

2. Impact of new antiretroviral combination therapies in HIV infected patients in Switzerland: prospective multicentre study

3. Plasma Viral Load and CD4+ Lymphocytes as Prognostic Markers of HIV-1 Infection

4. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies

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