\name{mrmr.cindex} \alias{mrmr.cindex} %- Also NEED an '\alias' for EACH other topic documented here. \title{Function to compute the concordance index for survival or binary class prediction} \description{ Function to compute the minimum redundancy - maximum relevance (mRMR) ranking for a risk prediction or a binary classification task based on the concordance index. The mRMR feature selection has been adapted to use the concordance index to estimate the correlation between a variable and the output (binary or survival) data. } \usage{ mrmr.cindex(x, surv.time, surv.event, cl, weights, comppairs=10, strat, alpha = 0.05, outx = TRUE, method = c("conservative", "noether", "nam"), alternative = c("two.sided", "less", "greater"), na.rm = FALSE) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{x}{a vector of risk predictions.} \item{surv.time}{a vector of event times.} \item{surv.event}{a vector of event occurence indicators.} \item{cl}{a vector of binary class indicators.} \item{weights}{weight of each sample.} \item{comppairs}{threshold for compairable patients.} \item{strat}{stratification indicator.} \item{alpha}{apha level to compute confidence interval.} \item{outx}{set to \code{TRUE} to not count pairs of observations tied on \code{x} as a relevant pair. This results in a Goodman-Kruskal gamma type rank correlation.} \item{method}{can take the value \code{conservative}, \code{noether} or \code{name} (see paper Pencina et al. for details).} \item{alternative}{a character string specifying the alternative hypothesis, must be one of \code{"two.sided"} (default), \code{"greater"} (concordance index is greater than 0.5) or \code{"less"} (concordance index is less than 0.5). You can specify just the initial letter.} \item{na.rm}{\code{TRUE} if missing values should be removed.} } %%\details{ %%} \note{ The "direction" of the concordance index (< 0.5 or > 0.5) is the opposite than the \link[Hmisc]{rcorr.cens} function in the \code{Hmisc} package. So you can easily get the same results than \link[Hmisc]{rcorr.cens} by changing the sign of \code{x}. } \value{ A mRMR ranking } \references{Harrel Jr, F. E. and Lee, K. L. and Mark, D. B. (1996) "Tutorial in biostatistics: multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing error", \emph{Statistics in Medicine}, \bold{15}, pages 361--387. Pencina, M. J. and D'Agostino, R. B. (2004) "Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation", \emph{Statistics in Medicine}, \bold{23}, pages 2109--2123, 2004.} \author{Benjamin Haibe-Kains, Markus Schroeder} %\note{ ~~further notes~~ } \seealso{\code{\link[Hmisc]{rcorr.cens}}, \code{\link[CPE]{phcpe}}, \code{\link[clinfun]{coxphCPE}}} \examples{ set.seed(12345) age <- rnorm(100, 50, 10) sex <- sample(0:1, 100, replace=TRUE) stime <- rexp(100) cens <- runif(100,.5,2) sevent <- as.numeric(stime <= cens) stime <- pmin(stime, cens) strat <- sample(1:3, 100, replace=TRUE) weight <- runif(100, min=0, max=1) comppairs <- 10 xx <- data.frame("age"=age, "sex"=sex) cat("survival prediction:\n") mrmr.cindex(x=xx, surv.time=stime, surv.event=sevent, strat=strat, weights=weight, method="noether", comppairs=comppairs) } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{survival} \keyword{univar}% __ONLY ONE__ keyword per line