| floodlight_2_by_continuous {kim} | R Documentation |
Floodlight 2 by Continuous
Description
Conduct a floodlight analysis for 2 x Continuous design.
Usage
floodlight_2_by_continuous(
data = NULL,
iv_name = NULL,
dv_name = NULL,
mod_name = NULL,
covariate_name = NULL,
interaction_p_include = TRUE,
iv_level_order = NULL,
output = "reg_lines_plot",
jitter_x_y_percent = 0,
jitter_x_percent = 0,
jitter_y_percent = 0,
dot_alpha = 0.5,
dot_size = 4,
interaction_p_value_font_size = 8,
jn_point_label_add = TRUE,
jn_point_font_size = 8,
jn_point_label_hjust = NULL,
lines_at_mod_extremes = FALSE,
interaction_p_vjust = -3,
plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt"),
legend_position = "right",
reg_line_types = c("solid", "dashed"),
jn_line_types = c("solid", "solid"),
jn_line_thickness = 1.5,
colors_for_iv = c("red", "blue"),
sig_region_color = "green",
sig_region_alpha = 0.08,
nonsig_region_color = "gray",
nonsig_region_alpha = 0.08,
x_axis_title = NULL,
y_axis_title = NULL,
legend_title = NULL,
round_decimals_int_p_value = 3,
line_of_fit_thickness = 1,
round_jn_point_labels = 2
)
Arguments
data |
a data object (a data frame or a data.table) |
iv_name |
name of the binary independent variable |
dv_name |
name of the dependent variable |
mod_name |
name of the continuous moderator variable |
covariate_name |
name of the variables to control for |
interaction_p_include |
logical. Should the plot include a p-value for the interaction term? |
iv_level_order |
order of levels in the independent
variable for legend. By default, it will be set as levels of the
independent variable ordered using R's base function |
output |
type of output (default = "reg_lines_plot"). Possible inputs: "interactions_pkg_results", "simple_effects_plot", "jn_points", "regions", "reg_lines_plot" |
jitter_x_y_percent |
horizontally and vertically jitter dots by a percentage of the respective ranges of x and y values. |
jitter_x_percent |
horizontally jitter dots by a percentage of the range of x values |
jitter_y_percent |
vertically jitter dots by a percentage of the range of y values |
dot_alpha |
opacity of the dots (0 = completely transparent,
1 = completely opaque). By default, |
dot_size |
size of the dots (default = 4) |
interaction_p_value_font_size |
font size for the interaction p value (default = 8) |
jn_point_label_add |
logical. Should the labels for Johnson-Neyman point labels be added to the plot? (default = TRUE) |
jn_point_font_size |
font size for Johnson-Neyman point labels (default = 8) |
jn_point_label_hjust |
a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points. |
lines_at_mod_extremes |
logical. Should vertical lines be drawn at the observed extreme values of the moderator if those values lie in siginificant region(s)? (default = FALSE) |
interaction_p_vjust |
By how much should the label for the
interaction p-value be adjusted vertically?
By default, |
plot_margin |
margin for the plot
By default |
legend_position |
position of the legend (default = "right").
If |
reg_line_types |
types of the regression lines for the two levels
of the independent variable.
By default, |
jn_line_types |
types of the lines for Johnson-Neyman points.
By default, |
jn_line_thickness |
thickness of the lines at Johnson-Neyman points (default = 1.5) |
colors_for_iv |
colors for the two values of the independent variable (default = c("red", "blue")) |
sig_region_color |
color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant. |
sig_region_alpha |
opacity for |
nonsig_region_color |
color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant. |
nonsig_region_alpha |
opacity for |
x_axis_title |
title of the x axis. By default, it will be set
as input for |
y_axis_title |
title of the y axis. By default, it will be set
as input for |
legend_title |
title of the legend. By default, it will be set
as input for |
round_decimals_int_p_value |
To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3) |
line_of_fit_thickness |
thickness of the lines of fit (default = 1) |
round_jn_point_labels |
To how many digits after the decimal point should the jn point labels be rounded? (default = 2) |
Details
The following package(s) must be installed prior to running this function: Package 'interactions' v1.1.1 (or possibly a higher version) by Jacob A. Long (2020), https://cran.r-project.org/package=interactions See the following references: Spiller et al. (2013) doi:10.1509/jmr.12.0420 Kim (2021) doi:10.5281/zenodo.4445388
Examples
# typical example
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec")
# add covariates
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec",
covariate_name = c("cyl", "hp"))
# adjust the jn point label positions
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec",
jn_point_label_hjust = c(1, 0))
# return regions of significance and nonsignificance
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec",
output = "regions")
# draw lines at the extreme values of the moderator
# if they are included in the significant region
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec",
lines_at_mod_extremes = TRUE)
#' # remove the labels for jn points
floodlight_2_by_continuous(
data = mtcars,
iv_name = "am",
dv_name = "mpg",
mod_name = "qsec",
jn_point_label_add = FALSE)