A Comparison of Baseline and Time-Dependent Approaches in Cox Model

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Simulation study highlights the impact of time-dependent covariates on hazard rate estimates, indicating bias in baseline measurements.

Baseline models often underestimate true covariate effects, particularly in scenarios with high measurement frequency.
The study shows that lower correlation decreases power in baseline models while increasing hazard rates mitigates underestimation.
Simulation data from 1,000 individuals revealed a progressive increase in relative bias with decreasing correlation between repeated measurements.
Future research will explore broader settings, considering the complexities of real-world data in environmental epidemiology.

Schiattarella et al. (2025) studied this question.

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View Full Paper

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Authors

Simulation study highlights the impact of time-dependent covariates on hazard rate estimates, indicating bias in baseline measurements.

Baseline models often underestimate true covariate effects, particularly in scenarios with high measurement frequency.
The study shows that lower correlation decreases power in baseline models while increasing hazard rates mitigates underestimation.
Simulation data from 1,000 individuals revealed a progressive increase in relative bias with decreasing correlation between repeated measurements.
Future research will explore broader settings, considering the complexities of real-world data in environmental epidemiology.

Schiattarella et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark