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Updated: May 20, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A transition model for quality-of-life data with non-ignorable non-monotone missing data
Kaijun Liao1, Derek R Freres, Andrea B Troxel
1Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. kliao@mail.med.upenn.edu
Abstract:
In this paper, we consider a full likelihood method to analyze continuous longitudinal responses with non-ignorable non-monotone missing data. We consider a transition probability model for the missingness mechanism. A first-order Markov dependence structure is assumed for both the missingness mechanism and observed data. This process fits the natural data structure in the longitudinal framework. Our main interest is in estimating the parameters of the marginal model and evaluating the missing-at-random assumption in the Effects of Public Information Study, a cancer-related study recently conducted at the University of Pennsylvania. We also present a simulation study to assess the performance of the model.
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