Joint Modeling of Longitudinal and Survival Data
نویسندگان
چکیده
منابع مشابه
Bayesian Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data
A longitudinal study refers to collection of a response variable and possibly some explanatory variables at multiple follow-up times. In many clinical studies with longitudinal measurements, the response variable, for each patient is collected as long as an event of interest, which considered as clinical end point, occurs. Joint modeling of continuous longitudinal measurements and survival time...
متن کاملJoint modeling of longitudinal categorical data and survival data
In many biomedical studies, it is of interest to study the covariate effect on both longitudinal categorical outcomes and survival outcomes. For example, in cancer research, it is of interest to study the treatment effect on both quality of life which is a categorical outcome measured longitudinally and survival time. In this talk, we will discuss such joint models. Random effects are introduce...
متن کاملJoint modeling of survival and longitudinal data: likelihood approach revisited.
The maximum likelihood approach to jointly model the survival time and its longitudinal covariates has been successful to model both processes in longitudinal studies. Random effects in the longitudinal process are often used to model the survival times through a proportional hazards model, and this invokes an EM algorithm to search for the maximum likelihood estimates (MLEs). Several intriguin...
متن کاملJoint Modeling of Longitudinal and Cure-survival Data.
This article presents semiparametric joint models to analyze longitudinal measurements and survival data with a cure fraction. We consider a broad class of transformations for the cure-survival model, which includes the popular proportional hazards structure and the proportional odds structure as special cases. We propose to estimate all the parameters using the nonparametric maximum likelihood...
متن کاملDiscussion on 'Joint modeling of survival and longitudinal non-survival data' by Gould et al.
First, we would like to congratulate the authors on a very accurate and clearly written work. The paper provides a thorough literature review on various aspects of the joint model and certainly provides a strong motivation to the use of joint modeling techniques in medical applications. Jointly modelling two or more processes together has been an active area of research for quite sometime now. ...
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ژورنال
عنوان ژورنال: The Stata Journal: Promoting communications on statistics and Stata
سال: 2013
ISSN: 1536-867X,1536-8734
DOI: 10.1177/1536867x1301300112