Package: hdcuremodels 0.0.2

hdcuremodels: Penalized Mixture Cure Models for High-Dimensional Data

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.

Authors:Han Fu [aut], Kellie J. Archer [aut, cre]

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hdcuremodels.pdf |hdcuremodels.html✨
hdcuremodels/json (API)

# Install 'hdcuremodels' in R:

install.packages('hdcuremodels', repos = c('https://kelliejarcher.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kelliejarcher/hdcuremodels/issues

Datasets:

amltest - AML test data
amltrain - AML training data

On CRAN:

4.54 score 5 scripts 132 downloads 10 exports 100 dependencies

Last updated 2 days agofrom:2e03b116b1. Checks:5 OK, 2 NOTE, 2 ERROR. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 31 2025
R-4.5-win	NOTE	Mar 31 2025
R-4.5-mac	ERROR	Mar 31 2025
R-4.5-linux	NOTE	Mar 31 2025
R-4.4-win	OK	Mar 31 2025
R-4.4-mac	OK	Mar 31 2025
R-4.4-linux	OK	Mar 31 2025
R-4.3-win	OK	Mar 31 2025
R-4.3-mac	ERROR	Mar 31 2025

Exports:auc_mcm concordance_mcm cure_estimate cureem curegmifs cv_cureem cv_curegmifs generate_cure_data nonzerocure_test sufficient_fu_test

Dependencies:abind assertthat backports bbmle bdsmatrix BH boot broom car carData cli codetools colorspace corpcor corrplot cowplot cpp11 data.table Deriv deSolve doBy doParallel dplyr fansi farver fastGHQuad flexsurv flexsurvcure foreach Formula generics ggplot2 ggpubr ggrepel ggsci ggsignif glmnet glue gridExtra gtable gtools isoband iterators knockoff labeling lattice lifecycle lme4 magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr mstate muhaz munsell mvnfast mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig plyr polynom purrr quadprog quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack Rdsdp reformulas rlang RSpectra rstatix rstpm2 scales shape SparseM statmod stringi stringr survival tibble tidyr tidyselect utf8 vctrs viridisLite withr

hdcuremodels-vignette

Rendered fromhdcuremodels.Rmdusingknitr::rmarkdownon Mar 31 2025.

Last update: 2025-03-21
Started: 2025-03-21

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
AML test data	amltest
AML training data	amltrain
AUC for cure prediction using mean score imputation	auc_mcm
Extract model coefficients from a fitted mixture cure object	coef.mixturecure coefficients
C-statistic for mixture cure models	concordance_mcm
Estimate cured fraction	cure_estimate
Fit penalized mixture cure model using the E-M algorithm	cureem
Fit penalized parametric mixture cure model using the GMIFS algorithm	curegmifs
Fit penalized mixture cure model using the E-M algorithm with cross-validation for parameter tuning	cv_cureem
Fit a penalized parametric mixture cure model using the GMIFS algorithm with cross-validation for model selection	cv_curegmifs
Simulate data under a mixture cure model	generate_cure_data
Non-parametric pest for a non-zero cured fraction	nonzerocure_test
Plot fitted mixture cure model	plot.mixturecure
Predicted probabilities for susceptibles, linear predictor for latency, and risk class for latency for mixture cure fit	predict.mixturecure
Print the contents of a mixture cure fitted object	print.mixturecure
Test for sufficient follow-up	sufficient_fu_test
Summarize a Fitted Mixture Cure Object.	summary.mixturecure