Abstract
The authors propose the local likelihood method for the time-varying coefficient additive hazards model. They use the Newton-Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time-varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data from a laryngeal cancer clinical study.
| Original language | English |
|---|---|
| Pages (from-to) | 321-337 |
| Number of pages | 17 |
| Journal | Canadian Journal of Statistics |
| Volume | 35 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2007 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Additive model
- Asymptotic normality
- Censored data
- Local polynomial
- Maximum likelihood
- Nonparametric estimation
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