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Plot a dependent variable versus concentration

Source: R/plot_dvconc.R
plot_dvconc.Rd

Unlike plot_dvtime() and plot_gof(), this function does not filter dose rows internally. Pre-filter the input to observation rows (typically by CMT or EVID == 0) before calling — see the example below.

Usage

plot_dvconc(
  data,
  dv_var = "DV",
  idv_var = "CONC",
  col_var = NULL,
  col_trend = FALSE,
  loess = TRUE,
  linear = FALSE,
  se_loess = FALSE,
  se_linear = FALSE,
  ref = NULL,
  log_y = FALSE,
  show_caption = TRUE,
  theme = NULL,
  ...
)

Arguments

data

Input dataset. Must contain only observation rows (no dose records). Filter by CMT or EVID == 0 before passing.

dv_var

Column containing the dependent variable. Accepts bare names or strings. Default is DV.

idv_var

Independent variable column. Accepts bare names or strings. Default is CONC.

col_var

Column to map to the color aesthetic. Accepts bare names or strings. Default is NULL.

col_trend

Logical indicating if the variable specified in col_var should be used to stratify trend lines

loess

Logical indicating if a loess smoother fit should be shown. Default is TRUE

linear

Logical indicating if a linear regression fit should be shown. Default is FALSE.

se_loess

Logical indicating if the standard error should be shown for the loess fit. Default is FALSE

se_linear

Logical indicating if the standard error should be shown for the linear fit. Default is FALSE

ref

Numeric y-intercept for a horizontal reference line, or NULL for no reference line. For example, ref = 0 draws a baseline reference for change-from-baseline data.

log_y

Logical indicator for log10 transformation of the y-axis.

show_caption

Logical indicating if a caption should be shown describing the data plotted

theme

Theme object created by plot_dvconc_theme(). Defaults can be viewed by running plot_dvconc_theme() with no arguments.

...

Additional arguments passed to geom_smooth()

Value

A ggplot2 plot object

See also

Other exploratory analysis: plot_dvconc_theme(), plot_dvtime(), plot_dvtime_theme()

Examples

data_sad_pd <- dplyr::filter(data_sad, CMT ==3)
data <- dplyr::mutate(data_sad_pd, Dose = var_addn(DOSE, ID, sep = "mg"))
plot_dvconc(data, dv_var = ODV, idv_var = CONC, col_var = Dose, col_trend = FALSE)
#> Warning: `col_var` colors observations but trend lines are not stratified. Set `col_trend = TRUE` to stratify trend lines by color.
#> `geom_smooth()` using formula = 'y ~ x'