The main function
SurvRegCens 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 (
WeibullDiag), inference for the mean difference of two arbitrarily censored Normal samples (
NormalMeanDiffCens), and estimation of canonical parameters from censored samples for several distributional assumptions (
Stanislas Hubeaux (maintainer), [email protected]
We thank Sarah Haile for contributing the functions
WeibullDiag to the package.
Hubeaux, S. (2013). Estimation from left- and/or interval-censored samples. Technical report, Biostatistics Oncology, F. Hoffmann-La Roche Ltd.
Hubeaux, S. (2013). Parametric Surival Regression Model with left- and/or interval-censored covariate. Technical report, Biostatistics Oncology, F. Hoffmann-La Roche Ltd.
Hubeaux, S. and Rufibach, K. (2014). SurvRegCensCov: Weibull Regression for a Right-Censored Endpoint with a Censored Covariate. Preprint, http://arxiv.org/abs/1402.0432.
Lynn, H. S. (2001). Maximum likelihood inference for left-censored HIV RNA data. Stat. Med., 20, 33–45.
Sattar, A., Sinha, S. K. and Morris, N. J. (2012). A Parametric Survival Model When a Covariate is Subject to Left-Censoring. Biometrics & Biostatistics, S3(2).
# The main functions in this package are illustrated in their respective help files.
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