Pages that link to "Item:Q652366"
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The following pages link to Risk prediction for prostate cancer recurrence through regularized estimation with simultaneous adjustment for nonlinear clinical effects (Q652366):
Displaying 11 items.
- A stochastic approach to risk management for prostate cancer patients on active surveillance (Q1786034) (← links)
- The log-beta Weibull regression model with application to predict recurrence of prostate cancer (Q1935686) (← links)
- Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters (Q2032189) (← links)
- Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic (Q2827205) (← links)
- Model-free scoring system for risk prediction with application to hepatocellular carcinoma study (Q3119829) (← links)
- Variable selection in high-dimensional partly linear additive models (Q3145401) (← links)
- Rank-based estimation in the ℓ1-regularized partly linear model for censored outcomes with application to integrated analyses of clinical predictors and gene expression data (Q3304984) (← links)
- A group bridge approach for component selection in nonparametric accelerated failure time additive regression model (Q5079492) (← links)
- Estimation of the optimal regime in treatment of prostate cancer recurrence from observational data using flexible weighting models (Q5283324) (← links)
- Assessing predictive accuracy of survival regressions subject to nonindependent censoring (Q6627316) (← links)
- Variable selection for high-dimensional partly linear additive Cox model with application to Alzheimer's disease (Q6627590) (← links)
