High-Dimensional Cure Models
AUC for cure prediction using mean score imputation
Extract model coefficients from a fitted mixturecure object
C-statistic for mixture cure models
Estimate cured fraction
Fit penalized mixture cure model using the E-M algorithm
Fit penalized parametric mixture cure model using the GMIFS algorithm
Fit penalized mixture cure model using the E-M algorithm with cross-va...
Fit a penalized parametric mixture cure model using the generalized mo...
Dimension method for mixturecure objects
Return model family and fitting algorithm for mixturecure model fits
Extract model formula for mixturecure object
Simulate data under a mixture cure model
hdcuremodels: High-Dimensional Cure Models
Log-likelihood for fitted mixture cure model
Number of observations in mixturecure object
Non-parametric test for a non-zero cured fraction
Number of parameters in fitted mixture cure model
Plot fitted mixture cure model
Predicted probabilities for susceptibles, linear predictor for latency...
Print the contents of a mixture cure fitted object
Test for sufficient follow-up
Summarize a fitted mixture cure object
Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022)<doi:10.1002/sim.9513> and Archer et al (2024)<doi:10.1186/s13045-024-01553-6>. False discovery rate controlled variable selection is provided using model-X knock-offs.
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