Adaptive Cox Proportional Hazards
The Adaptive Cox Proportional Hazards model extends the classic Cox regression for time-to-event outcomes by adding adaptive LASSO (or related) penalization. It simultaneously estimates hazard ratios and performs variable selection, shrinking irrelevant covariate coefficients exactly to zero. This makes it especially valuable in high-dimensional clinical or genomic datasets where the number of candidate predictors is large relative to the number of events.
Kilderegistrering
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- Zhang, H. H., & Lu, W. (2007). Adaptive Lasso for Cox's proportional hazards model. Biometrika, 94(3), 691–703. · DOI 10.1093/biomet/asm037
- Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. · DOI 10.1111/j.2517-6161.1972.tb00899.x
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