Dear all, I am new to R and may make beginner mistakes. Sorry.
I am learning using R to do survival analysis. As a start I used the example script code provided in the documentation of predict.survreg of the survival package: # Draw figure 1 from Escobar and Meeker fit <- survreg(Surv(time,status) ~ age + age^2, data=stanford2, dist='lognormal') plot(stanford2$age, stanford2$time, xlab='Age', ylab='Days', xlim=c(0,65), ylim=c(.01, 10^6), log='y') pred <- predict(fit, newdata=list(age=1:65), type='quantile', p=c(.1, .5, .9)) matlines(1:65, pred, lty=c(2,1,2), col=1) When I compare the graphical output with Fig. 1 of Escobar and Meeker (1992), I find that my output produces quantiles that are sloping down linearly with age. The quantiles in Fig. 1 of Escobar and Meeker (1992) however are obviously non-linear. I compared this with the corresponding section in the S-Plus manual and found that the R and S-Plus are virtually identical (as they should) and that the predicted quantiles in S-Plus (Fig. 31.3) are also non-linear. I checked the obvious help files and R-archive and found nothing on this. I must be making a very basic mistake but can't find it. Your feedback would be highly appreciated. Best, Michael Ref: Escobar and Meeker (1992). Assessing influence in regression analysis with censored data. Biometrics, 48, 507-528. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
