View source: R/floodlight_for_contrasts.R
| floodlight_for_contrasts | R Documentation | 
Conduct a floodlight analysis for a set of contrasts with a continuous moderator variable.
floodlight_for_contrasts(
  data = NULL,
  iv_name = NULL,
  dv_name = NULL,
  mod_name = NULL,
  contrasts = NULL,
  contrasts_for_floodlight = NULL,
  covariate_name = NULL,
  interaction_p_include = TRUE,
  iv_category_order = NULL,
  heteroskedasticity_consistent_se = "HC4",
  round_r_squared = 3,
  round_f = 2,
  sigfigs = 2,
  jn_points_disregard_threshold = NULL,
  print_floodlight_plots = TRUE,
  output = "reg_lines_plot",
  jitter_x_percent = 0,
  jitter_y_percent = 0,
  dot_alpha = 0.5,
  dot_size = 4,
  interaction_p_value_font_size = 6,
  jn_point_font_size = 6,
  jn_point_label_hjust = NULL,
  interaction_p_vjust = -3,
  plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt"),
  legend_position = "right",
  line_of_fit_types = c("solid", "dashed"),
  line_of_fit_thickness = 1.5,
  jn_line_types = c("solid", "solid"),
  jn_line_thickness = 1.5,
  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,
  round_jn_point_labels = 2
)
| data | a data object (a data frame or a data.table) | 
| iv_name | name of the multicategorical independent variable; this variable must have three or more categories. | 
| dv_name | name of the dependent variable | 
| mod_name | name of the continuous moderator variable | 
| contrasts | names of the contrast variables | 
| contrasts_for_floodlight | names of the contrast variables for which floodlight analyses will be conducted | 
| 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_category_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  | 
| heteroskedasticity_consistent_se | which kind of heteroskedasticity-consistent (robust) standard errors should be calculated? (default = "HC4") | 
| round_r_squared | number of decimal places to which to round r-squared values (default = 3) | 
| round_f | number of decimal places to which to round the f statistic for model comparison (default = 2) | 
| sigfigs | number of significant digits to round to
(for values in the regression tables, except for p values).
By default  | 
| jn_points_disregard_threshold | the Minimum Distance in
the unit of the moderator variable that will be used for various purposes,
such as (1) to disregard the second Johnson-Neyman point
that is different from the first Johnson-Neyman (JN) point by
less than the Minimum Distance; (2) to determine regions of
significance, which will calculate the p-value of the IV's effect
(the focal dummy variable's effect) on DV at a candidate
JN point + / - the Minimum Distance.
This input is hard to explain, but a user can enter a really low value
for this argument (e.g.,  | 
| print_floodlight_plots | If  | 
| output | output of the function (default = "all"). Possible inputs: "reg_models", "reg_tables", "reg_tables_rounded", "all" | 
| 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_font_size | font size for Johnson-Neyman point labels (default = 6) | 
| 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. | 
| 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  | 
| line_of_fit_types | types of the lines of fit for the two levels
of the independent variable.
By default,  | 
| line_of_fit_thickness | thickness of the lines of fit (default = 1.5) | 
| 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) | 
| 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) | 
| round_jn_point_labels | To how many digits after the decimal point should the jn point labels be rounded? (default = 2) | 
See the following reference, which covers a related topic: Hayes & Montoya (2017) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/19312458.2016.1271116")}
## Not run: 
# typical example
# copy and modify the 'mtcars' data
mtcars2 <- setDT(data.table::copy(mtcars))
# make sure the data table package is attached
mtcars2[, contrast_1 := fcase(cyl == 4, -2, cyl %in% c(6, 8), 1)]
mtcars2[, contrast_2 := fcase(cyl == 4, 0, cyl == 6, 1, cyl == 8, -1)]
floodlight_for_contrasts(
data = mtcars2,
iv_name = "cyl",
dv_name = "mpg",
mod_name = "qsec",
contrasts = paste0("contrast_", 1:2),
contrasts_for_floodlight = "contrast_2")
## End(Not run)
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