\name{hr.comp2} \alias{hr.comp2} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Function to statistically compare two hazard ratios (alternative interface) } \description{ This function compares two hazard ratios from their betas and standard errors as computed by a Cox model for instance. The statistical test is a Student t test for dependent samples. The two hazard ratios must be computed from the same survival data. } \usage{ hr.comp2(x1, beta1, se1, x2, beta2, se2, n) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{x1}{ risk score used to estimate the first hazard ratio. } \item{beta1}{ beta estimate for the first hazard ratio. } \item{se1}{ standard error of beta estimate for the first hazard ratio. } \item{x2}{ risk score used to estimate the second hazard ratio. } \item{beta2}{ beta estimate for the second hazard ratio. } \item{se2}{ standard error of beta estimate for the first hazard ratio. } \item{n}{ number of samples from which the hazard ratios were estimated. } } \details{ The two hazard ratios must be computed from the same samples (and corresponding survival data). The function uses a Student t test for dependent samples. } \value{ \item{p.value }{p-value from the Student t test for the comparison beta1 > beta2 (equivalently hr1 > hr2)} \item{hr1 }{value of the first hazard ratio} \item{hr2 }{value of the second hazard ratio} } \references{ Student 1908) "The Probable Error of a Mean", \emph{Biometrika}, \bold{6}, 1, pages 1--25. Haibe-Kains, B. and Desmedt, C. and Sotiriou, C. and Bontempi, G. (2008) "A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?", \emph{Bioinformatics}, \bold{24}, 19, pages 2200--2208. } \author{ Benjamin Haibe-Kains } %\note{} \seealso{ \code{\link[survival]{coxph}}, \code{\link{t.test}} } \examples{ require(survival) set.seed(12345) age <- as.numeric(rnorm(100, 50, 10) >= 50) size <- as.numeric(rexp(100,1) > 1) stime <- rexp(100) cens <- runif(100,.5,2) sevent <- as.numeric(stime <= cens) stime <- pmin(stime, cens) coxm1 <- coxph(Surv(stime, sevent) ~ age) coxm2 <- coxph(Surv(stime, sevent) ~ size) hr.comp2(x1=age, beta1=coxm1$coefficients, se1=drop(sqrt(coxm1$var)), x2=size, beta2=coxm2$coefficients, se2=drop(sqrt(coxm2$var)), n=100) } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ survival } \keyword{ htest }% __ONLY ONE__ keyword per line