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.
Thiébaut, Rodolphe
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. [electronic resource] - Statistics in medicine Jan 2005 - 65-82 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
0277-6715
10.1002/sim.1923 doi
Anti-HIV Agents--therapeutic use
Antiretroviral Therapy, Highly Active--standards
CD4 Lymphocyte Count
Cohort Studies
HIV Infections--drug therapy
HIV-1--genetics
Humans
Longitudinal Studies
Models, Biological
Models, Statistical
Patient Dropouts
RNA, Viral--blood
Substance Abuse, Intravenous
Viral Load
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. [electronic resource] - Statistics in medicine Jan 2005 - 65-82 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
0277-6715
10.1002/sim.1923 doi
Anti-HIV Agents--therapeutic use
Antiretroviral Therapy, Highly Active--standards
CD4 Lymphocyte Count
Cohort Studies
HIV Infections--drug therapy
HIV-1--genetics
Humans
Longitudinal Studies
Models, Biological
Models, Statistical
Patient Dropouts
RNA, Viral--blood
Substance Abuse, Intravenous
Viral Load