Plot a dose-proportionality assessment via power law (log-log) regression

Usage

plot_doseprop(
  data,
  metrics,
  metric_var = "PPTESTCD",
  exp_var = "PPORRES",
  dose_var = "DOSE",
  method = "normal",
  ci = 0.95,
  sigdigits = 3,
  se = TRUE
)

Arguments

data: Input dataset for log-log regression. Default expected format is output from PKNCA::pk.nca() (i.e., SDTM PP formatting)
metrics: character vector of exposure metrics in data to plot
metric_var: character string of variable in data containing the values provided in metrics. Default is "PPTESTCD".
exp_var: Character string specifying the variable in data containing the exposure metric (dependent variable) Default is "PPORRES".
dose_var: Character string specifying the variable in data containing the dose (independent variable) Default is "DOSE".
method: character string specifying the distribution to be used to derived the confidence interval. Options are "normal" (default) and "tdist"
ci: confidence interval to be calculated. Options are 0.95 (default) and 0.90
sigdigits: number of significant digits for rounding
se: logical to display confidence interval around regression. Default is TRUE.

Value

a ggplot plot object

Examples

plot_doseprop(dplyr::filter(data_sad_nca, PART == "Part 1-SAD"), metrics = c("aucinf.obs", "cmax"))