Related Experiment Video
Updated: May 2, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian
A Lawrence Gould1, Mark Ernest Boye2, Michael J Crowther3
1Merck Research Laboratories, 351 North Sumneytown Pike, North Wales, PA 19454, U.S.A.
Abstract:
Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Statistical Methods for Analyzing Epidemiological Data

