R/interaction_plot.R

In jasonmoy28/psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R

#' Interaction plot 
#' 
#' `r lifecycle::badge("stable")` \cr
#' The function creates interaction plot. By default, it will create an interaction plot using -1 SD and +1 SD of continuous variables, or the two levels of binary variables. 
#' 
#'
#' @param model a regression model object from \link[effects]{effect}.
#' @param interaction_term default is the first highest order interaction term in the model. The term should be given explicitly if you want to plot other interaction terms.
#' @param response_var_name The name of the response variable can be changed using this setting. 
#' @param predict_var1_name The name of the first predictor can be changed using this setting. 
#' @param predict_var2_name The name of the second predictor can be changed using this setting. 
#' @param predict_var3_name The name of the third predictor can be changed using this setting. 
#' @param predict_var1_level The default is -1 SD and +1 SD for a continuous variable, and it is the two levels for a binary variable. These can be changed using this setting.
#' @param predict_var2_level The default is -1 SD and +1 SD for a continuous variable, and it is the two levels for a binary variable. These can be changed using this setting.
#' @param predict_var3_level The default is -1 SD and +1 SD for a continuous variable, and it is the two levels for a binary variable. These can be changed using this setting.
#' @param predict_var1_level_name The labels of the level can be change using this value (e.g., `c('-1 SD','+1 SD')`). The order should be from the left to right on the x-axis. 
#' @param predict_var2_level_name The labels of the level can be change using this value (e.g., `c('-1 SD','+1 SD')`). The order should be from the top to down on the legend. 
#' @param predict_var3_level_name The labels of the level can be change using this value (e.g., `c('-1 SD','+1 SD')`). The order should be from the left to right on the facets. 
#' @param y_lim the plot's upper and lower limit for the y-axis. Length of 2. Example: `c(lower_limit, upper_limit)`
#' @param plot_color default if `FALSE`. Set to `TRUE` if you want to plot in color
#' @param return_plot_data default is `FALSE`. Set to `TRUE` to return the plot data.
#' @param return_plot default is `FALSE`. Set to `TRUE` to return the plot.
#' @param print_plot default is `TRUE`. Set to `TRUE` to print the plot. 
#' @param verbose deafult is `TRUE`.
#' @param data Optional data.frame. Only used when it is not possible to extract data from the model object. 
#'
#' @return a `ggplot` object
#' @export
#'
#' @examples
#' 
#' model_1 <- lm(Sepal.Length ~ Petal.Width * Sepal.Width,
#'               data = iris)
#' interaction_plot(model_1)
#' 
#' model_2 <- lm(Sepal.Length ~ Petal.Width * Sepal.Width * Petal.Length,
#'               data = iris
#' )
#' 
#' interaction_plot(model_2, # it will automatically select the first three-way interaction term
#' 
#'                  # change the name of the variables of the plot
#'                  response_var_name = 'SEPAL LENGTH',
#'                  predict_var1_name = 'PETAL WIDTH',
#'                  predict_var2_name = 'SEPAL WIDTH',
#'                  predict_var3_name = 'PETAL LENGTH',
#'                            
#'                  # change the number of levels of the variables (e.g., adding the mean)
#'                  predict_var1_level = c(0.43, 1.19,1.96), 
#'                  predict_var2_level = c(2.62, 3.05,3.49), 
#'                  predict_var3_level = c(1.99,3.758,5.52),
#'                  predict_var1_level_name = c('-1 SD','Mean','+1 SD'),
#'                  predict_var2_level_name = c('-1 SD','Mean','+1 SD'),
#'                  predict_var3_level_name = c('-1 SD','Mean','+1 SD')) 

interaction_plot = function(model,
                            interaction_term = NULL,
                            response_var_name = NULL,
                            predict_var1_name = NULL,
                            predict_var2_name = NULL,
                            predict_var3_name = NULL,
                            predict_var1_level = NULL,
                            predict_var2_level = NULL,
                            predict_var3_level = NULL,
                            predict_var1_level_name = NULL,
                            predict_var2_level_name = NULL,
                            predict_var3_level_name = NULL,
                            y_lim = NULL,
                            plot_color = FALSE,
                            return_plot_data = FALSE,
                            return_plot = FALSE,
                            verbose = TRUE,
                            print_plot = TRUE,
                            data = NULL){
  
  
  interaction_term_exist = model %>% insight::find_interactions() %>% .$conditional
  three_way_interaction_exist = length(interaction_term_exist[stringr::str_detect(":.+:", string = interaction_term_exist)])
  if (three_way_interaction_exist == 0) {
    two_way_interaction_plot(model,
                             interaction_term = interaction_term,
                             response_var_name = response_var_name,
                             predict_var1_name = predict_var1_name,
                             predict_var2_name = predict_var2_name,
                             predict_var1_level = predict_var1_level,
                             predict_var2_level = predict_var2_level,
                             predict_var1_level_name = predict_var1_level_name,
                             predict_var2_level_name = predict_var2_level_name,
                             y_lim = y_lim,
                             plot_color = plot_color,
                             return_plot_data = return_plot_data,
                             return_plot = return_plot,
                             verbose = verbose,
                             print_plot = print_plot,
                             data = data)
    
  } else if (three_way_interaction_exist != 0) {
    three_way_interaction_plot(model,
                             interaction_term = interaction_term,
                             response_var_name = response_var_name,
                             predict_var1_name = predict_var1_name,
                             predict_var2_name = predict_var2_name,
                             predict_var3_name = predict_var3_name,
                             predict_var1_level = predict_var1_level,
                             predict_var2_level = predict_var2_level,
                             predict_var3_level = predict_var3_level,
                             predict_var1_level_name = predict_var1_level_name,
                             predict_var2_level_name = predict_var2_level_name,
                             predict_var3_level_name = predict_var3_level_name,
                             y_lim = y_lim,
                             plot_color = plot_color,
                             return_plot_data = return_plot_data,
                             return_plot = return_plot,
                             verbose = verbose,
                             print_plot = print_plot,
                             data = data)
  }
}