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SurvRegCensCov (version 1.3)

Weibull Regression for a Right-Censored Endpoint with Interval-Censored Covariate

Description

The main function of this package allows estimation of a Weibull Regression for a right-censored endpoint, one interval-censored covariate, and an arbitrary number of non-censored covariates. Additional functions allow to switch between different parametrizations of Weibull regression used by different R functions, inference for the mean difference of two arbitrarily censored Normal samples, and estimation of canonical parameters from censored samples for several distributional assumptions.

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Version

Install

install.packages('SurvRegCensCov')

Monthly Downloads

353

Version

1.3

License

GPL (>= 2)

Maintainer

Stanislas Hubeaux

Last Published

April 24th, 2014

Functions in SurvRegCensCov (1.3)

Log-likelihood functions for estimation of canonical parameters from a censored sample

Extract value of log-likelihood at maximum for Weibull regression with an interval-censored covariate

Print result of Weibull regression with an interval-censored covariate

Extract coefficients of Weibull regression with an interval-censored covariate

Weibull Survival Regression Model with a censored covariate

Survival Times of Larynx Cancer Patients

LoglikWeibullSurvRegCens

Log-likelihood function of a Weibull Survival Regression Model allowing for an interval-censored covariate.

Summarizing Weibull regression with an interval-censored covariate

Censor a vector of continuous numbers

Weibull Regression for Survival Data

NormalMeanDiffCens

Maximum Likelihood Estimator for the mean difference between two censored normally distributed samples

ParamSampleCens

Maximum Likelihood Estimator of parameters from a censored sample

TimeSampleWeibull

Generate time-to-event data according to a Weibull regression model

SurvRegCensCov-package

Weibull Regression for a Right-Censored Endpoint with Interval-Censored Covariates

LoglikNormalDeltaCens

Log likelihood function to compute mean difference between two normally distributed censored samples.

Transformation of survreg output for the Weibull distribution

Cumulative distribution function

Diagnostic Plot of Adequacy of Weibull Distribution

WeibullIntegrate

Function to be integrated in function SurvRegCens