erplots

The erplots package provides a mini-language for building exposure-response plots: model curves/ribbons, quantile-binned response-rate summaries, data strips, and grouped distribution panels. It is model-agnostic: erplots never fits a model itself. Instead, you fit a model with whatever package suits your workflow (e.g. erglm for logistic regression), and pass the fitted object to er_plot_add_model().

Installation

You can install the development version of erplots like so:

pak::pak("djnavarro/erplots")

Example

library(erplots)
library(erglm)

mod <- erglm_model(ae1 ~ aucss, erglm_data, family = binomial())

erglm_data |> 
  er_plot(aucss, ae1) |> 
  er_plot_add_model(mod) |> 
  er_plot_add_quantiles() |> 
  er_plot_add_groups(aucss) |> 
  plot()

mod2 <- erglm_model(ae2 ~ aucss + sex, erglm_data, family = binomial())

plt <- erglm_data |> 
   er_plot(aucss, ae2, stratify_by = sex) |> 
   er_plot_add_model(mod2) |> 
   er_plot_add_quantiles(bins = 3) |> 
   er_plot_add_data() |> 
   er_plot_add_groups(group_by = c(aucss, treatment), keep_strata = FALSE)

print(plt)
#> <er_plot>
#>   plot variables:
#>     - exposure:        aucss
#>     - response:        ae2
#>     - stratification:  sex
#>   plot layers:
#>     - model:           erglm_model/glm/lm
#>     - quantile:        3 bins
#>     - overlay:         stratified
#>     - group:           .aucss_quantile, treatment
#>   plots built: <none>
#>   output built: no
plot(plt)