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survidm: Inference and Prediction in an Illness-Death Model

survidm is an R package which introduces 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.

Installation

survidm is available through both CRAN and GitHub.

Get the released version from CRAN:

install.packages("survidm")

Or the development version from GitHub:

# install.packages("devtools")
devtools::install_github("sestelo/survidm")

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Version

Install

install.packages('survidm')

Monthly Downloads

191

Version

1.3.2

License

GPL-3

Maintainer

Marta Sestelo

Last Published

June 24th, 2021

Functions in survidm (1.3.2)

PKMW

Presmoothed Kaplan-Meier weights
coxidm

Fit proportional hazards regression model in each transition of the Illness-Death Model.
summary.survIDM

Summarizing fits of survIDM class
nevents

Count number of observed transitions.
summary.cmm

Summarizing fits of cmm class
markov.test

This function is used to test the markov assumption in the illness-death model.
colonIDM

Chemotherapy for Stage B/C colon cancer.
tprob

Nonparametric estimation of transition probabilities in the illness-death model
sojourn

Nonparametric estimation of the Sojourn time distributions in the recurrence state in the illness-death model
plot.survIDM

Plot for an object of class "survIDM".
survIDM

Create a survIDM object
survidm-package

survidm: survidm
LLW

Local linear weights
Beran

Estimation of the conditional distribution function of the response, given the covariate under random censoring.
autoplot.survIDM

Visualization of objects of class survIDM with ggplot2 graphics.
CIF

Nonparametric estimation of the Cumulative Incident Functions in the illness-death model
bladderIDM

Bladder Cancer Recurrences.
KM

Kaplan-Meier product-limit estimate of survival
PKM

Presmoothed Kaplan-Meier product-limit estimate of survival
NWW

Nadaraya-Watson weights.
KMW

Kaplan-Meier weights