The goal of pmplots is to create exploratory and diagnostic plots commonly used in pharmacometrics.
You can install the released version of pmplots from MPN with:
mpn <- "https://mpn.metworx.com/snapshots/stable/2021-06-20"
install.packages("pmplots", repos = mpn)This installs from a specific, dated snapshot. Please check https://mpn.metworx.com/docs/snapshots/ for the most recent snapshot date.
You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("metrumresearchgroup/pmplots")library(pmplots)
library(dplyr)
data <- pmplots_data_obs()The default pmplots behavior is to expect names following NONMEM
convention, for example DV refers to observed values, PRED refers to
population predicted values. With that convention, we can easily make
observed versus predicted plots
dv_pred(data, yname = "MyDrug (ng/ml)")
dv_pred(data, loglog = TRUE)
npde_time(data)
npde_pred(data)
cwres_q(data)
id <- pmplots_data_id()
cont_cat(id, x = "STUDYc", y = c("WT", "SCR", "AAG")) %>% pm_grid()
pairs_plot(id, y = c("WT//Weight (kg)", "SCR//Creat (mg/dL)", "BMI//BMI (kg/m2)"))
wrap_cont_time(data, y = c("RES","WRES", "CWRES", "NPDE"), ncol = 2)
A functions and features (code + output) listing is available at pmplots_complete.md.
Consider installing the cowplot package to help arranging plots on a page. Also, consider installing latex2exp to allow you to use latex in axis titles.