Package: hdcuremodels 0.0.6

Kellie J. Archer

hdcuremodels: High-Dimensional Cure Models

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], Tung Lam Nguyen [rev], Panagiotis Papastamoulis [rev]

hdcuremodels_0.0.6.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hdcuremodels/json (API)

# Install 'hdcuremodels' in R:

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

Reviews:rOpenSci Software Review #692

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

Pkgdown/docs site:https://docs.ropensci.org

Datasets:

amltest - AML test data
amltrain - AML training data
pediatric_flt3 - Pediatric acute myeloid leukemia patients with FLT3-ITD rearrangement data

On CRAN:

4.60 score 10 scripts 647 downloads 10 exports 106 dependencies

Last updated from:466902cdc6 (on main). Checks:1 FAIL, 3 OK, 6 ERROR. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	FAIL	180
pkgdown docs	OK	238
source / vignettes	OK	265
linux-release-x86_64	ERROR	411
macos-release-arm64	ERROR	236
macos-oldrel-arm64	ERROR	232
windows-devel	ERROR	407
windows-release	ERROR	419
windows-oldrel	ERROR	441
wasm-release	OK	137

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 farver fastGHQuad flexsurv flexsurvcure foreach forecast Formula fracdiff generics ggplot2 ggpubr ggrepel ggsci ggsignif glmnet glue gridExtra gtable gtools isoband iterators knockoff labeling lattice lifecycle lme4 lmtest lsoda magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr mstate muhaz 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 S7 scales shape SparseM statmod stringi stringr survival tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Estimating Cure Models in High Dimensions: A Guide with hdcuremodels

Rendered fromhdcuremodels.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2025-03-21

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 mixturecure 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 generalized monotone incremental forward stagewise (GMIFS) algorithm (Hastie et al 2007) with cross-validation for model selection	cv_curegmifs
Dimension method for mixturecure objects	dim.mixturecure
Return model family and fitting algorithm for mixturecure model fits	family.mixturecure
Extract model formula for mixturecure object	formula.mixturecure
Simulate data under a mixture cure model	generate_cure_data
Log-likelihood for fitted mixture cure model	logLik.mixturecure
Number of observations in mixturecure object	nobs.mixturecure
Non-parametric test for a non-zero cured fraction	nonzerocure_test
Number of parameters in fitted mixture cure model	npar_mixturecure
Pediatric acute myeloid leukemia patients with FLT3-ITD rearrangement data	pediatric_flt3
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

Package: hdcuremodels 0.0.6

hdcuremodels: High-Dimensional Cure Models

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Help Manual

Usage by other packages (reverse dependencies)