Joint Models of Longitudinal and Time-to-Event Data Using Gibbs Sampling
نویسنده
چکیده
Jointly modelling related longitudinal and time-to-event data can offer advantages over separate modelling. We consider three models for longitudinal/time-to-event data: 1. random slopes and intercepts/constant hazard 2. random slopes and intercepts/step function hazard 3. random intercepts, fixed slope and IOU errors/constant hazard. Methods for simulating data from these models are outlined. We use Gibbs sampling to estimate the parameters. The models are fit using existing software (WinBUGS) and some original programs. The performance of the software is studied using simulated data.
منابع مشابه
کاربرد مدل توأم بقا و داده های طولی در بیماران دیالیز صفاقی
Background and Aim: In many medical studies along with longitudinal data, which are repeatedly measured during a certain time period, survival data are also recorded. In these situations, using models such as, mixed effects models or GEE method for longitudinal data and Cox model for survival data, are not appropriate because some necessary assumptions are not met. Instead, the joint models hav...
متن کاملBayesian 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 کاملSemi-parametric Quantile Regression for Analysing Continuous Longitudinal Responses
Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...
متن کاملمدلسازی توام داده‌های بقا و طولی و کاربرد آن در بررسی عوامل موثر بر آسیب حاد کلیوی
Background: In many clinical trials and medical studies, the survival and longitudinal data are collected simultaneously. When these two outcomes are measured from each subject and the survival variable depends on a longitudinal biomarker, using joint modelling of survival and longitudinal outcomes is a proper choice for analyzing the available data. Methods: In this retrospective archiv...
متن کاملBayesian Quantile Regression with Adaptive Elastic Net Penalty for Longitudinal Data
Longitudinal studies include the important parts of epidemiological surveys, clinical trials and social studies. In longitudinal studies, measurement of the responses is conducted repeatedly through time. Often, the main goal is to characterize the change in responses over time and the factors that influence the change. Recently, to analyze this kind of data, quantile regression has been taken ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003