ertte is the time-to-event member of the exposure-response (E-R) package family, alongside erglm (GLM E-R models) and emaxnls (Emax / logistic-Emax models), all of which plug into erplots for visualisation. It wraps survival::survreg()-based parametric accelerated failure time (AFT) modelling behind a tidy, consistent interface: model fitting, AIC-based distribution selection, stepwise covariate modelling, and simulation.
Installation
You can install the development version of ertte from GitHub with:
# install.packages("pak")
pak::pak("djnavarro/ertte")Example
library(ertte)
mod <- ertte_model(survival::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 × 13
#> id sex age weight dose treatment aucss cmaxss time event
#> <int> <fct> <int> <dbl> <dbl> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 1 Female 27 70 200 Drug 1114. 187. 30 1
#> 2 1 Female 27 70 200 Drug 1114. 187. 60 1
#> 3 1 Female 27 70 200 Drug 1114. 187. 90 1
#> 4 2 Female 27 59 100 Drug 561. 49.1 30 0
#> 5 2 Female 27 59 100 Drug 561. 49.1 60 0
#> 6 2 Female 27 59 100 Drug 561. 49.1 90 0
#> 7 3 Female 24 65 0 Placebo 0 0 30 0
#> 8 3 Female 24 65 0 Placebo 0 0 60 0
#> 9 3 Female 24 65 0 Placebo 0 0 90 0
#> 10 4 Female 29 63 0 Placebo 0 0 30 0
#> 11 4 Female 29 63 0 Placebo 0 0 60 0
#> 12 4 Female 29 63 0 Placebo 0 0 90 0
#> 13 5 Male 27 91 200 Drug 1416. 143. 30 1
#> 14 5 Male 27 91 200 Drug 1416. 143. 60 1
#> 15 5 Male 27 91 200 Drug 1416. 143. 90 1
#> # ℹ 3 more variables: fit_survival <dbl>, ci_lower <dbl>, ci_upper <dbl>