This is an R package that implements the method of Rank Preserving Strucutural Failure Time models to estimate causal effects in failure time models in randomised control trials where participants do not comply with the treatment assigned.
As an example:
library(rpsftm)
?immdef
#> starting httpd help server ...
#> done
fit <- rpsftm(Surv(progyrs, prog)~rand(imm,1-xoyrs/progyrs), data = immdef, censor_time = censyrs)
summary(fit)
#> arm rx.Min. rx.1st Qu. rx.Median rx.Mean rx.3rd Qu. rx.Max.
#> 1 0 0.0000000 0.0000000 0.0000000 0.1574062 0.2547779 0.9770941
#> 2 1 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> Length Class Mode
#> psi 1 -none- numeric
#> fit 14 survfit list
#> CI 2 -none- numeric
#> Sstar 2000 Surv numeric
#> rand 2000 rand numeric
#> ans 5 -none- list
#> eval_z 2 data.frame list
#> n 2 table numeric
#> obs 2 -none- numeric
#> exp 2 -none- numeric
#> var 4 -none- numeric
#> chisq 1 -none- numeric
#> call 4 -none- call
#> formula 3 terms call
#> terms 3 terms call
#>
#> psi: -0.1810871
#> exp(psi): 0.8343627
#> Confidence Interval, psi -0.3496948 0.002042503
#> Confidence Interval, exp(psi) 0.7049032 1.002045
plot(fit)
The main function is rpsftm which returns an object that has print, summary, and plot S3 methods.
See the vignette rpsftm_vignette for further details, explanation and examples.