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.

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)

These 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.