R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # A short test on coxph.detail, to ensure that the computed hazard is > # equal to the theoretical value > library(survival) > aeq <- function(a,b) all.equal(as.vector(a), as.vector(b)) > > # taken from book4.R > test2 <- data.frame(start=c(1, 2, 5, 2, 1, 7, 3, 4, 8, 8), + stop =c(2, 3, 6, 7, 8, 9, 9, 9,14,17), + event=c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0), + x =c(1, 0, 0, 1, 0, 1, 1, 1, 0, 0) ) > > byhand <- function(beta, newx=0) { + r <- exp(beta) + loglik <- 4*beta - (log(r+1) + log(r+2) + 2*log(3*r+2) + 2*log(3*r+1) + + log(2*r +2)) + u <- 1/(r+1) + 1/(3*r+1) + 2*(1/(3*r+2) + 1/(2*r+2)) - + ( r/(r+2) +3*r/(3*r+2) + 3*r/(3*r+1)) + imat <- r*(1/(r+1)^2 + 2/(r+2)^2 + 6/(3*r+2)^2 + + 6/(3*r+1)^2 + 6/(3*r+2)^2 + 4/(2*r +2)^2) + + hazard <-c( 1/(r+1), 1/(r+2), 1/(3*r+2), 1/(3*r+1), 1/(3*r+1), + 1/(3*r+2), 1/(2*r +2) ) + + + # The matrix of weights, one row per obs, one col per time + # deaths at 2,3,6,7,8,9 + wtmat <- matrix(c(1,0,0,0,1, 0, 0,0,0,0, + 0,1,0,1,1, 0, 0,0,0,0, + 0,0,1,1,1, 0, 1,1,0,0, + 0,0,0,1,1, 0, 1,1,0,0, + 0,0,0,0,1, 1, 1,1,0,0, + 0,0,0,0,0, 1, 1,1,1,1, + 0,0,0,0,0,.5,.5,1,1,1), ncol=7) + wtmat <- diag(c(r,1,1,r,1,r,r,r,1,1)) %*% wtmat + + x <- c(1,0,0,1,0,1,1,1,0,0) + status <- c(1,1,1,1,1,1,1,0,0,0) + xbar <- colSums(wtmat*x)/ colSums(wtmat) + n <- length(x) + + # Table of sums for score and Schoenfeld resids + hazmat <- wtmat %*% diag(hazard) #each subject's hazard over time + dM <- -hazmat #Expected part + for (i in 1:5) dM[i,i] <- dM[i,i] +1 #observed + dM[6:7,6:7] <- dM[6:7,6:7] +.5 # observed + mart <- rowSums(dM) + + # Table of sums for score and Schoenfeld resids + # Looks like the last table of appendix E.2.1 of the book + resid <- dM * outer(x, xbar, '-') + score <- rowSums(resid) + scho <- colSums(resid) + + # We need to add the ties back up (they are symmetric) + scho[6:7] <- rep(mean(scho[6:7]), 2) + + list(loglik=loglik, u=u, imat=imat, xbar=xbar, haz=hazard* exp(beta*newx), + mart=mart, score=score, rmat=resid, + scho=scho) + } > > # The actual coefficient of the fit is close to zero. Using a larger > # number pushes the test harder, but it should still work without > # the init and iter arguments, i.e., for any coefficient. > fit1 <- coxph(Surv(start, stop, event) ~x, test2,init=-1, iter=0) > temp <- coxph.detail(fit1) > temp2 <- byhand(fit1$coef, fit1$means) > aeq(temp$haz, c(temp2$haz[1:5], sum(temp2$haz[6:7]))) [1] TRUE > > > proc.time() user system elapsed 0.89 0.07 0.96