plot_design | R Documentation |
Takes the output from generate()
or long_format()
, and plots conditions' distributions on numeric variables used in the generate pipeline (i.e. indepdent variables, controls). Alternatively, distributions of any numeric variables in the original dataframe can be queried.
plot_design(
df,
include = "design",
dodge_width = 0.1,
point_size = 0.5,
line_width = 1,
force = TRUE,
id_col = "string"
)
df |
Output from |
include |
A character vector indicating which variables to include in the plot. This can be those specified by |
dodge_width |
The width to give to |
point_size |
Size of points (default = 0.75) |
line_width |
Thickness of lines (default = 1) |
force |
Logical, should the function be forced to try and work if attributes are missing (default is |
id_col |
A character vector specifying the column identifying unique observations (e.g. in |
A ggplot object showing how conditions differ in independent variables, and are matched for in controls.
stim <- lexops |>
dplyr::filter(PK.Brysbaert >= .75) |>
split_by(BG.SUBTLEX_UK, 0.001:0.003 ~ 0.009:0.011) |>
split_by(CNC.Brysbaert, 1:2 ~ 4:5) |>
control_for(Zipf.SUBTLEX_UK, -0.2:0.2) |>
control_for(Length) |>
generate(n = 50, match_null = "balanced")
plot_design(stim)
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