The 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 (ConvertWeibull, WeibullReg, 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 (ParamSampleCens).
Stanislas Hubeaux (maintainer), stan.hubeaux@bluewin.ch
Kaspar Rufibach, kaspar.rufibach@gmail.com
http://www.kasparrufibach.ch
We thank Sarah Haile for contributing the functions ConvertWeibull, WeibullReg, WeibullDiag to the package.
| Package: | SurvRegCensCov |
| Type: | Package |
| Version: | 1.7 |
| Date: | 2023-09-27 |
| License: | GPL (>=2) |
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, https://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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