Joint modeling of longitudinal and event time data: application to HIV study
Open Access
- 1 January 2013
- journal article
- Published by Herbert Publications PVT LTD in Journal of Medical Statistics and Informatics
- Vol. 1 (1), 1
- https://doi.org/10.7243/2053-7662-1-1
Abstract
Many clinical studies generate a dataset having longitudinal repeated biomarker measurement data and time to an event data, which often depend on each other. In such studies, characteristics of the pattern of a biomarkerKeywords
This publication has 34 references indexed in Scilit:
- Treatment of Death in the Analysis of Longitudinal Studies of Gerontological OutcomesThe Journals of Gerontology: Series A, 2010
- On Estimating the Relationship between Longitudinal Measurements and Time‐to‐Event Data Using a Simple Two‐Stage ProcedureBiometrics, 2010
- Effect of Trajectories of Glycemic Control on Mortality in Type 2 Diabetes: A Semiparametric Joint Modeling ApproachAmerican Journal of Epidemiology, 2010
- Joint Modeling of Longitudinal Changes in Depressive Symptoms and Mortality in a Sample of Community-Dwelling Elderly PeoplePsychosomatic Medicine, 2009
- Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approachBiostatistics, 2009
- Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration ApproachBiometrics, 2008
- Application of a Joint Multivariate Longitudinal–Survival Analysis to Examine the Terminal Decline Hypothesis in the Swiss Interdisciplinary Longitudinal Study on the Oldest OldThe Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 2008
- Individualized Predictions of Disease Progression Following Radiation Therapy for Prostate CancerJournal of Clinical Oncology, 2005
- A Joint Model for Longitudinal Data Profiles and Associated Event Risks with Application to a Depression StudyJournal of the Royal Statistical Society Series C: Applied Statistics, 2005
- Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDSJournal of the American Statistical Association, 1995