Abstract
A method for fitting piecewise exponential regression models to censored survival data is described. Stratification is performed recursively, using a combination of statistical tests and residual analysis. The splitting criterion employed in cross‐validation is the average squared error of the residuals. The bootstrap is employed to keep the probability of a type I error (the error of discovering two or more strata when there is only one) of the method close to a predetermined value. The proposed method can thus also serve as a formal goodness‐of‐fit test for the exponential regression model. Real and simulated data are used for illustration.
| Original language | English |
|---|---|
| Pages (from-to) | 43-61 |
| Number of pages | 19 |
| Journal | Biometrical Journal |
| Volume | 36 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1994 |
Keywords
- Bootstrap
- Exponential regression
- Recursive partitioning
- Survival analysis
Fingerprint
Dive into the research topics of 'Tree‐Structured Exponential Regression Modeling'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver