Plot a dependent variable versus concentration

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,
  cfb = FALSE,
  cfb_base = 0,
  ylab = "Response",
  xlab = "Drug Concentration",
  log_y = FALSE,
  log_x = FALSE,
  show_caption = TRUE,
  theme = NULL,
  ...
)

Arguments

data: Input dataset.
dv_var: Column containing the DV variable in data. Accepts bare names or strings.
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
cfb: Logical indicating if dependent variable is a change from baseline. Plots a reference line at y = cfb_baseline. Default is FALSE.
cfb_base: Value for y-intercept when cfb = TRUE. Default is 0.
ylab: Character string specifying the y-axis label: Default is "Response".
xlab: Character string specifying the x-axis label: Default is "Drug Concentration"
log_y: Logical indicator for log10 transformation of the y-axis.
log_x: Logical indicator for log10 transformation of the x-axis.
show_caption: Logical indicating if a caption should be show describing the data plotted
theme: Named list of aesthetic parameters to be supplied to the plot. Defaults can be viewed by running plot_dvconc_theme() with no arguments.
...: Additional arguments passed to geom_smooth()

Value

A ggplot2 plot object

Examples

data_sad_pd <- dplyr::filter(data_sad, CMT ==3)
data <- df_addn(dplyr::mutate(data_sad_pd, Dose = DOSE), grp_var = Dose, sep = "mg")
#> Joining with `by = join_by(Dose)`
plot_dvconc(data, dv_var = ODV, idv_var = CONC, col_var = Dose, col_trend = FALSE)
#> `geom_smooth()` using formula = 'y ~ x'