README

The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

smoothHR

Description

Provides flexible hazard ratio curves allowing non-linear relationships between continuous predictors and survival. To better understand the effects that each continuous covariate has on the outcome, results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. Confidence bands for these curves are also derived.

Installation

If you want to use the release version of the smoothHR package, you can install the package from CRAN as follows:

install.packages(pkgs="smoothHR");

If you want to use the development version of the smoothHR package, you can install the package from GitHub via the remotes package:

remotes::install_github(
  repo="arturstat/smoothHR",
  build=TRUE,
  build_manual=TRUE
);

Authors

Funding

This research was financed by FEDER Funds through Programa Operacional Factores de Competitividade – COMPETE; by Portuguese Funds through FCT – Fundação para a Ciência e a Tecnologia, in the form of grants PTDC/MAT/104879/2008 and Est-C/MAT/UI0013/2011; and by the Spanish Ministry of Industry and Innovation, Grant MTM2011-28285-C02-01.

References

Cadarso-Suarez, C. and Meira-Machado, L. and Kneib, T. and Gude, F. (2010). Flexible hazard ratio curves for continuous predictors in multi-state models: an application to breast cancer data. Statistical Modelling, 10(3), 291-314. doi:10.1177/1471082X0801000303

Eilers, Paul H. and Marx, Brian D. (1996). Flexible smoothing with B-splines and penalties. Statistical Science, 11(2), 89-121. doi:10.1214/ss/1038425655

Hosmer, D. W. and Lemeshow, S. and May, S. (2008). Applied Survival Analysis: Regression Modeling of Time to Event Data: Second Edition, John Wiley and Sons Inc., New York, NY.

Hurvich, C. M. and Simonoff, J. S. and Tsai, Chih-Ling (1998). Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. JRSSB, 60(2), 271–293. doi:10.1111/1467-9868.00125

Meira-Machado, L. and Cadarso-Suárez, C. and Gude, F. and Araújo, A. (2013). smoothHR: An R Package for Pointwise Nonparametric Estimation of Hazard Ratio Curves of Continuous Predictors. Computational and Mathematical Methods in Medicine, 2013, 11 pages. doi:10.1155/2013/745742

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.