The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Provides tools for working with exposure-response models for time-to-event data. It is designed with a similar interface to the erglm and emaxnls packages, and supports the plotting interface supplied by the erplots package. It provides two model-fitting engines, one for parametric AFT regression models and another for semi-parametric Cox proportional-hazards regression, behind a shared, tidy interface for survival-probability prediction, restricted mean survival time, landmark analysis, stepwise covariate modelling, and simulation.
You can install the development version of ertte from GitHub with:
# install.packages("pak")
pak::pak("djnavarro/ertte")library(ertte)
mod <- ertte_aft(Surv(time, event) ~ aucss, ertte_data)
mod
#> Call:
#> survival::survreg(formula = formula, data = data, dist = dist)
#>
#> Coefficients:
#> (Intercept) aucss
#> 4.8563375087 -0.0006407913
#>
#> Scale= 0.7164032
#>
#> Loglik(model)= -1207.3 Loglik(intercept only)= -1263.9
#> Chisq= 113.25 on 1 degrees of freedom, p= <2e-16
#> n= 300
ertte_predict(mod, ertte_data[1:5, ], time = c(30, 60, 90))
#> # A tibble: 15 × 14
#> id sex age weight dose treatment aucss cmaxss time event admin_censor fit_survival ci_lower ci_upper
#> <int> <fct> <int> <dbl> <dbl> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 Female 27 70 200 Drug 1114. 187. 30 1 180 0.701 0.666 0.733
#> 2 1 Female 27 70 200 Drug 1114. 187. 60 1 180 0.393 0.344 0.441
#> 3 1 Female 27 70 200 Drug 1114. 187. 90 1 180 0.193 0.152 0.237
#> 4 2 Female 27 59 100 Drug 561. 49.1 30 0 180 0.805 0.780 0.827
#> 5 2 Female 27 59 100 Drug 561. 49.1 60 0 180 0.565 0.521 0.607
#> 6 2 Female 27 59 100 Drug 561. 49.1 90 0 180 0.366 0.317 0.416
#> 7 3 Female 24 65 0 Placebo 0 0 30 0 180 0.877 0.856 0.895
#> 8 3 Female 24 65 0 Placebo 0 0 60 0 180 0.708 0.665 0.747
#> 9 3 Female 24 65 0 Placebo 0 0 90 0 180 0.544 0.487 0.598
#> 10 4 Female 29 63 0 Placebo 0 0 30 0 180 0.877 0.856 0.895
#> 11 4 Female 29 63 0 Placebo 0 0 60 0 180 0.708 0.665 0.747
#> 12 4 Female 29 63 0 Placebo 0 0 90 0 180 0.544 0.487 0.598
#> 13 5 Male 27 91 200 Drug 1416. 143. 30 1 180 0.628 0.584 0.669
#> 14 5 Male 27 91 200 Drug 1416. 143. 60 1 180 0.294 0.242 0.347
#> 15 5 Male 27 91 200 Drug 1416. 143. 90 1 180 0.116 0.0824 0.155These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.