Description Details Author(s) References

Contains functions to estimate the Correlation-Adjusted Regression Survival (CARS) Scores.
The main function is `carSurvScore`

, which estimates CARS scores of each variable.
The higher the absolute values of CARS scores, the higher the variable importance.
Additionally there is the function `carVarSelect`

to select cut-off thresholds
to separate variables associated with survival from noise variables. There are two possible
cut-off threshold options: False non-discovery rate q-values and empirical quantiles of the
raw scores.

Package: carSurv

Type: Package

Version: 1.0.0

Date: 2018-02-24

License: GPL-3

Thomas Welchowski (Maintainer) welchow@imbie.meb.uni-bonn.de

Welchowski, T. and Zuber, V. and Schmid, M., (2018), Correlation-Adjusted Regression Survival Scores for High-Dimensional Variable Selection, <arXiv:1802.08178>

Zuber, V. and Strimmer, K., (2011), High-Dimensional Regression and Variable Selection Using CAR Scores, Statistical Applications in Genetics and Molecular Biology

Schaefer, J. and Strimmer, K., (2005), A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics, Statistical Applications in Genetics and Molecular Biology

Van der Laan, M. J. and Robins, J. M., (2003), Unified Methods for Censored Longitudinal Data and Causality, Springer Series in Statistics Strimmer, K., (2008), A unified approach to false discovery rate estimation, BMC Bioinformatics

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