Sampling survival probabilities

[jrdnmdhl]

Would be useful to have a way to generate a set of survival probabilities based on drawing a new set of parameters from mvnorm. This can effectively be done right now by taking either the lower or upper bound of the following:

testit = flexsurvreg(Surv(rectime,censrec)~group,data=bc,dist="weibull")
summary(testit, t=c(500,100),type="survival",ci=0.5,B=1,tidy=T)

But producing it this way is a bit of a kluge, so it would be good to have a more direct way of generating this.

[chjackson]

Does this do what you want, or do I misunderstand? This gives a sample of 10 alternative values for the 365-day survival probability, based on 10 random draws from the asymptotic normal distribution of the parameter estimates.

testit <- flexsurvreg(Surv(rectime,censrec)~group,data=bc,dist="weibull")
pars <- normboot.flexsurvreg(testit, B=10, newdata=list(group="Medium"))
testit$dfns$p(365, pars[,1], pars[,2], lower.tail=FALSE)

[jrdnmdhl]

The goal here is to produce survival probabilities at arbitrary times, but based on a single draw from the distribution of parameters. This might be necessary, for example, to run a single simulation of a probabilistic sensitivity analysis in a partitioned survival model, To slightly modify your example:

testit <- flexsurvreg(Surv(rectime,censrec)~group,data=bc,dist="weibull")
pars <- normboot.flexsurvreg(testit, B=1, newdata=list(group="Medium"))
testit$dfns$p(seq(from=0, to=1000, by=100), pars[,1], pars[,2], lower.tail=FALSE)

To have this functionality packaged as an S3 generic, like summary.flexsurvreg, would be useful.

[chjackson]

OK - I think it would be a worthwhile enhancement to summary.flexsurvreg to have the option to return a sample of B values for any required summary statistic, rather than a point estimate or a CI.

[t-patton]

Along similar lines to the comment by jrdnmdhl, is there any way that the pmatrix.fs() command can be adapted to draw from the distribution of parameters, in the case of a multistate model, for the purposes of a probabilistic sensitivity analysis?

[chjackson]

@t-patton The code for pmatrix.fs actually does this sampling if you request a confidence interval. It calls the function bootci.fmsm, which draws a sample, calculates the P matrix (or some other function) and takes their quantiles to get the confidence interval. You may be able to tweak these functions to get what you want - but I agree a user interface would be nice.

[kkmann]

Would be great to extend this (essentially parametric bootstrap?) to sim.fmsm and simulate.flexsurvreg - I think at the moment they do not consider parameter uncertainty, right? Edit: So, to generate predictions under paramter uncertainty, one would currently have to use boot or rsample packages to bootstrap the fitting itself. Quite expensive.