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condSURV: Estimation of the Conditional Survival Function for Ordered Multivariate Failure Time Data

condSURV is an R package to implement some newly developed methods for the estimation of the conditional survival function. The package implements three nonparametric and semiparametric estimators for these quantities. The package also implements feasible estimation methods for these quantities conditionally on current or past covariate measures.

Other related estimators are also implemented in the package. One of these estimators is the Kaplan-Meier estimator typically assumed to estimate the survival function. A modification of the Kaplan-Meier estimator, based on a preliminary estimation (presmoothing) of the censoring probability for the survival time, given the available information is also implemented.

Installation

condSURV is available through both CRAN and GitHub.

Get the released version from CRAN:

install.packages("condSURV")

Or the development version from GitHub:

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

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Version

Install

install.packages('condSURV')

Monthly Downloads

455

Version

2.0.4

License

GPL (>= 2)

Maintainer

Marta Sestelo

Last Published

March 1st, 2023

Functions in condSURV (2.0.4)

NWW

Nadaraya-Watson weights.
PKM

Presmoothed Kaplan-Meier product-limit estimate of survival.
Beran

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

Kaplan-Meier product-limit estimate of survival.
KMW

Kaplan-Meier weights.
colonCS

Chemotherapy for Stage B/C colon cancer.
condSURV-package

condSURV:A package for nonparametric estimation of the survival functions for ordered multivariate failure time data.
LLW

Local linear weights.
gbcsCS

German Breast Cancer Study Data.
plot.survCS

Plot for an object of class "survCS".
PKMW

Presmoothed Kaplan-Meier weights.
survCS

Create a survCS object.
summary.survCS

Summarizing fits of survCS class
survCOND

Conditional survival probabilities based on the Kaplan-Meier weights, Landmark approaches and Inverse probability of censoring weighted.
bladderCS

Bladder Cancer Recurrences.