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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   1000   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.