Dear R-Helpers, I am hoping to perform survival analyses using the "ex-Gaussian" distribution. I understand that the ex-Gaussian is a convolution of exponential and Gaussian distributions for survival data.
I checked the "survreg.distributions" help and saw that it is possible to mix pre-defined distributions. Am I correct to think that the following code makes the ex-Gaussian:- exGauss=survreg.distributions$exponential exGauss$name='exGaussian' exGauss$dist=survreg.distributions$gaussian Am I further correct to think that I can compare the fits of the ex-Gaussian and Weibull distributions to the data via:- fit1=survreg(Surv(response)~1+frailty(unit), data=dat, dist=exGauss) fit2=survreg(Surv(response)~1+frailty(unit), data=dat, dist='weibull') anova(fit1, fit2) Finally, am I further correct to think that the output from this anova means that the Weibull distribution fits the data worse than the exGauss distribution that I made? Terms Resid. Df -2*LL Test Df Deviance P(>|Chi|) 1 1 + frailty(unit) 4229.778 63129.46 NA NA NA 2 1 + frailty(unit) 4228.020 58426.27 = 1.757815 4703.190 0 Many thanks for your help with these questions. I have a feeling they are trivial, but I am a psychiatrist so I need to check that I am not barking up the wrong tree (or simply barking...)! Jonathan Williams PS why does "weibull" need quotes in the survreg procedure, while exGauss does not? ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html