Package: survidm 1.3.2

survidm: Inference and Prediction in an Illness-Death Model

Newly developed methods for the estimation of several probabilities in an illness-death model. The package can be used to obtain nonparametric and semiparametric estimates for: transition probabilities, occupation probabilities, cumulative incidence function and the sojourn time distributions. Additionally, it is possible to fit proportional hazards regression models in each transition of the Illness-Death Model. Several auxiliary functions are also provided which can be used for marginal estimation of the survival functions.

Authors:Luis Meira-Machado, Marta Sestelo and Gustavo Soutinho

survidm_1.3.2.tar.gz
survidm_1.3.2.zip(r-4.7-x86_64)survidm_1.3.2.zip(r-4.7-arm64)survidm_1.3.2.zip(r-4.6-x86_64)survidm_1.3.2.zip(r-4.6-arm64)survidm_1.3.2.zip(r-4.5-x86_64)
survidm_1.3.2.tgz(r-4.6-x86_64)survidm_1.3.2.tgz(r-4.6-arm64)survidm_1.3.2.tgz(r-4.5-x86_64)survidm_1.3.2.tgz(r-4.5-arm64)
survidm_1.3.2.tar.gz(r-4.7-arm64)survidm_1.3.2.tar.gz(r-4.7-x86_64)survidm_1.3.2.tar.gz(r-4.6-arm64)survidm_1.3.2.tar.gz(r-4.6-x86_64)
survidm_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
survidm/json (API)

# Install 'survidm' in R:

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

Bug tracker:https://github.com/sestelo/survidm/issues

Datasets:

bladderIDM - Bladder Cancer Recurrences.
colonIDM - Chemotherapy for Stage B/C colon cancer.

On CRAN:

3.62 score 1 stars 1 packages 28 scripts 316 downloads 19 exports 85 dependencies

Last updated from:1638cf1008. Checks:13 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	143
linux-devel-x86_64	NOTE	195
source / vignettes	OK	262
linux-release-arm64	NOTE	141
linux-release-x86_64	NOTE	196
macos-release-arm64	NOTE	147
macos-release-x86_64	NOTE	451
macos-oldrel-arm64	NOTE	150
macos-oldrel-x86_64	NOTE	306
windows-devel-arm64	NOTE	389
windows-devel-x86_64	NOTE	175
windows-release-arm64	NOTE	382
windows-release-x86_64	NOTE	140
windows-oldrel-x86_64	NOTE	120
wasm-release	OK	112

Exports:autoplot Beran CIF coxidm KM KMW LLW markov.test nevents NWW PKM PKMW plot.survIDM print.survIDM sojourn summary.cmm summary.survIDM survIDM tprob

Dependencies:askpass base64enc boot bslib cachem cli codetools cpp11 crosstalk crs cubature curl data.table digest doParallel doRNG dplyr evaluate farver fastmap fontawesome foreach fs generics ggplot2 glue gridExtra gtable highr htmltools htmlwidgets httr isoband iterators jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval lifecycle magrittr MASS Matrix MatrixModels memoise mime np openssl otel pillar pkgconfig plotly promises purrr quadprog quantreg R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rngtools S7 sass scales SparseM stringi stringr survival sys tibble tidyr tidyselect tinytex TPmsm utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
survidm: Inference and Prediction in an Illness-Death Model	survidm-package survidm
Visualization of objects of class 'survIDM' with ggplot2 graphics.	autoplot autoplot.survIDM
Estimation of the conditional distribution function of the response, given the covariate under random censoring.	Beran
Bladder Cancer Recurrences.	bladderIDM
Nonparametric estimation of the Cumulative Incident Functions in the illness-death model	CIF
Chemotherapy for Stage B/C colon cancer.	colonIDM
Fit proportional hazards regression model in each transition of the Illness-Death Model.	coxidm
Kaplan-Meier product-limit estimate of survival	KM
Kaplan-Meier weights	KMW
Local linear weights	LLW
This function is used to test the markov assumption in the illness-death model.	markov.test
Count number of observed transitions.	nevents
Nadaraya-Watson weights.	NWW
Presmoothed Kaplan-Meier product-limit estimate of survival	PKM
Presmoothed Kaplan-Meier weights	PKMW
Plot for an object of class "survIDM".	plot.survIDM
Nonparametric estimation of the Sojourn time distributions in the recurrence state in the illness-death model	sojourn
Summarizing fits of 'cmm' class	print.cmm summary.cmm
Summarizing fits of 'survIDM' class	print.survIDM summary.survIDM
Create a survIDM object	survIDM
Nonparametric estimation of transition probabilities in the illness-death model	tprob

Package: survidm 1.3.2

survidm: Inference and Prediction in an Illness-Death Model

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