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Estimating stage occupation probabilities in non-Markov models.

Nina Gunnes¹, Ornulf Borgan, Odd O Aalen

¹Institute of Basic Medical Sciences, Department of Biostatistics, University of Oslo, P.O. Box 1122, Blindern, 0317, Oslo, Norway. nina.gunnes@medisin.uio.no

Lifetime Data Analysis

|March 6, 2007

Summary

This study compares two estimators for stage occupation probabilities in multistage models with dependent censoring. The Datta-Satten estimator is generally unbiased, while the Aalen-Johansen estimator can be biased but may have lower variability.

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Area of Science:

Biostatistics
Survival Analysis
Statistical Modeling

Background:

Dependent censoring complicates estimation in multistage models.
Covariate processes can link transition and censoring mechanisms.

Purpose of the Study:

To evaluate Datta-Satten and Aalen-Johansen estimators for stage occupation probabilities under dependent censoring.
To compare bias and variability of these estimators.

Main Methods:

Applied an additive hazard regression model to adjust for dependent censoring.
Utilized inverse probability of censoring weighting for observed processes.
Conducted simulation studies using frailty models.

Main Results:

The Datta-Satten estimator demonstrated approximate unbiasedness.

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The Aalen-Johansen estimator showed bias due to dependent censoring.

The Aalen-Johansen estimator exhibited slightly smaller mean squared error in simulations.

Conclusions:

The Datta-Satten estimator is reliable for stage occupation probability estimation.
Practical deviations between estimators require highly selective censoring mechanisms.