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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Matched survival data in a co-twin control design.
Mette Gerster1, Mia Madsen, Per Kragh Andersen
1Department of Biostatistics, University of Southern Denmark, Odense, Denmark, mgerster@health.sdu.dk.
Lifetime Data Analysis
|July 19, 2013
Summary
Violations in shared frailty models for twin studies can bias results. A fixed-effects survival model offers a robust alternative, providing accurate regression coefficient estimates even when independence assumptions are unmet.
Area of Science:
- Biostatistics
- Epidemiology
- Genetics
Background:
- The co-twin control design is valuable for analyzing event times in twin studies.
- Shared frailty models are used to account for within-pair associations in survival analysis.
- Standard shared frailty models assume independence between random effects and covariates.
Purpose of the Study:
- To investigate the impact of violating the independence assumption in shared frailty models.
- To propose and evaluate an alternative method for robust inference in twin survival analysis.
Main Methods:
- Simulation studies were conducted using data generated from a shared frailty model.
- The performance of standard shared frailty model inference was compared to a proposed fixed-effects survival model.
- Bias and consistency of regression coefficient estimates were assessed under various scenarios.
Main Results:
- Violations of the independence assumption in shared frailty models can lead to substantial bias in regression coefficient estimates.
- The proposed fixed-effects survival model yields consistent and asymptotically normal estimates.
- The fixed-effects model demonstrates robustness regardless of the independence assumption's validity.
Conclusions:
- The standard shared frailty model is sensitive to violations of the independence assumption.
- A fixed-effects survival model provides a reliable alternative for analyzing event times in co-twin control studies.
- Researchers should consider fixed-effects models for more accurate inference in twin survival data analysis.
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