Last data update: 2014.03.03

Data Source

R Release (3.2.3)
CranContrib
BioConductor
All

Data Type

Packages
Functions
Images
Data set

Classification

Results 1 - 6 of 6 found.
[1] < 1 > [1]  Sort:

gcerisk : Generalized Competing Event Model

Package: gcerisk
Type: Package
Title: Generalized Competing Event Model
Version: 16.1.3
Date: 2016-04-26
Author: Hanjie Shen <has072@ucsd.edu>, Ruben Carmona
<ruben.carmona13@gmail.com>, Loren Mell <lmell@ucsd.edu>
Maintainer: Hanjie Shen <shenhanjie0418@gmail.com>
Depends: survival, cmprsk, ggplot2,
Imports: stats
Description: Generalized competing event model based on Cox PH model and Fine-Gray model.
This function is designed to develop optimized risk-stratification methods for competing
risks data, such as described in:
1. Carmona R, Gulaya S, Murphy JD, Rose BS, Wu J, Noticewala S,McHale MT, Yashar CM, Vaida F,
and Mell LK.(2014) <DOI:10.1016/j.ijrobp.2014.03.047>. Validated competing event model for thestage I-II
endometrial cancer population. Int J Radiat Oncol Biol Phys.89:888-98.
2. Carmona R, Zakeri K, Green G, Hwang L, Gulaya S, Xu B, Verma R, Williamson CW, Triplett DP, Rose
BS, Shen H, Vaida F, Murphy JD, and Mell LK.(2016) <DOI:10.1200/JCO.2015.65.0739>. Improved method to stratify
elderly cancer patients at risk for competing events. J Clin Oncol.in press.
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-27 18:30:37 UTC; has072
Repository: CRAN
Date/Publication: 2016-04-28 00:52:33

● Data Source: CranContrib
● 0 images, 2 functions, 1 datasets
● Reverse Depends: 0

missDeaths : 'Correctly Analyse Disease Recurrence with Missing at Risk Information using Population Mortality'

Package: missDeaths
Date: 2015-08-08
Title: 'Correctly Analyse Disease Recurrence with Missing at Risk
Information using Population Mortality'
Version: 1.2
Authors@R: c(
person("Tomaz","Stupnik",role=c("aut","cre"), email="tomaz.stupnik@guest.arnes.si"),
person("Maja","Pohar Perme",role="aut", email="maja.pohar@mf.uni-lj.si"))
Maintainer: Tomaz Stupnik <tomaz.stupnik@guest.arnes.si>
Description: Implements two methods: a nonparametric risk adjustment and a data imputation method that use general population mortality tables to allow a correct analysis of time to disease recurrence.
License: GPL (>= 2)
Imports: Rcpp (>= 0.11.1), mitools
LinkingTo: Rcpp
Depends: survival, rms, relsurv, cmprsk
NeedsCompilation: yes
Packaged: 2015-08-08 22:54:55 UTC; tomaz
Author: Tomaz Stupnik [aut, cre],
Maja Pohar Perme [aut]
Repository: CRAN
Date/Publication: 2015-08-09 09:11:39

● Data Source: CranContrib
● 0 images, 5 functions, 1 datasets
● Reverse Depends: 0

crrp : Penalized Variable Selection in Competing Risks Regression

Package: crrp
Type: Package
Title: Penalized Variable Selection in Competing Risks Regression
Version: 1.0
Date: 2015-06-19
Author: Zhixuan Fu
Maintainer: Zhixuan Fu <zhixuan.fu@yale.edu>
Depends: survival, Matrix, cmprsk
Description: In competing risks regression, the proportional subdistribution hazards(PSH) model is popular for its direct assessment of covariate effects on the cumulative incidence function. This package allows for penalized variable selection for the PSH model. Penalties include LASSO, SCAD, MCP, and their group versions.
License: GPL (>= 2)
Packaged: 2015-06-19 22:39:06 UTC; Evie
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-06-20 00:56:59

● Data Source: CranContrib
● 0 images, 2 functions, 0 datasets
● Reverse Depends: 0

crrstep : Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model

Package: crrstep
Type: Package
Title: Stepwise Covariate Selection for the Fine & Gray Competing Risks
Regression Model
Version: 2015-2.1
Date: 2015-02.23
Author: Ravi Varadhan & Deborah Kuk
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>
Description: Performs forward and backwards stepwise regression for the Proportional subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection criteria. BICcr has a penalty of k = log(n*), where n* is the number of primary events.
Depends: cmprsk
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2015-02-23 20:33:47 UTC; rvaradh1
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-02-23 23:17:17

● Data Source: CranContrib
● Cran Task View: Survival
● 0 images, 2 functions, 0 datasets
● Reverse Depends: 0

crskdiag : Diagnostics for Fine and Gray Model

Package: crskdiag
Type: Package
Version: 1.0
Date: 2015-09-18
Title: Diagnostics for Fine and Gray Model
Author: Jianing Li
Maintainer: Jianing Li <kinger198549@gmail.com>
Depends: R (>= 3.0.0), cmprsk
Description: Provides the implementation of analytical and graphical approaches for checking the assumptions of the Fine and Gray model.
License: GPL (>= 2)
NeedsCompilation: yes
Repository: CRAN
Packaged: 2015-10-02 11:10:41 UTC; Jianing
Date/Publication: 2015-10-02 22:01:22

● Data Source: CranContrib
● 0 images, 8 functions, 2 datasets
● Reverse Depends: 0

currentSurvival : Estimation of CCI and CLFS Functions

Package: currentSurvival
Version: 1.0
Date: 2013-01-19
Title: Estimation of CCI and CLFS Functions
Author: Eva Janousova, Tomas Pavlik, Jiri Mayer, Ladislav Dusek
Maintainer: Eva Janousova <janousova@iba.muni.cz>
Depends: R (>= 2.13.0), survival, cmprsk
Description: The currentSurvival package contains functions for the
estimation of the current cumulative incidence (CCI) and the
current leukaemia-free survival (CLFS). The CCI is the
probability that a patient is alive and in any disease
remission (e.g. complete cytogenetic remission in chronic
myeloid leukaemia) after initiating his or her therapy (e.g.
tyrosine kinase therapy for chronic myeloid leukaemia). The
CLFS is the probability that a patient is alive and in any
disease remission after achieving the first disease remission.
License: GPL (>= 2)
Packaged: 2013-01-19 17:49:05 UTC; janousova
Repository: CRAN
Date/Publication: 2013-01-19 19:54:21

● Data Source: CranContrib
● Cran Task View: Survival
● 0 images, 16 functions, 1 datasets
● Reverse Depends: 0