###################
#Description:  This R code uses Mplus Automation R Package to 
#              save model summaries in MS Excel format at 3 decimal places
#Instructions: Search code for text 'USER' and update the folder information	      
#Writer:       Jonathon Little
#Date:	       2024
#Cite:         Little, J. (2024). MplusSummaryTable. (Version 1.0) [Computer software]. Retrieved from
               https://www.statpsychservices.com.au/resources
#Acknowledgments:  ChatGpt4 was used to help debug and refine this code.
###################

# Load necessary libraries
#install.packages("MplusAutomation")  # Uncomment if not installed
#install.packages("openxlsx")         # Uncomment if not installed

library(MplusAutomation)
library(openxlsx)

runModels_Interactive()

#####USER CHANGE FOLDER HERE######
# Define the folder containing your Mplus output files
folder_path <- "C:/Users/Jane Smith/"

# List all Mplus output files (.out files) in the folder
output_files <- list.files(folder_path, pattern = "\\.out$", full.names = TRUE)

# Initialize an empty list to store summaries
model_summaries_list <- list()

# Initialize a variable to store all column names
all_columns <- NULL

# Loop through each file and extract model summaries
for (file in output_files) {
  try({
    # Read the model output and extract summaries directly
    mplus_model_summaries <- readModels(file, what = "summaries")$summaries
    
    # If summaries are not NULL, process them
    if (!is.null(mplus_model_summaries)) {
      # Get the column names of the current summary
      current_columns <- colnames(mplus_model_summaries)
      
      # Update the all_columns variable with the union of all columns
      if (is.null(all_columns)) {
        all_columns <- current_columns
      } else {
        all_columns <- union(all_columns, current_columns)
      }
      
      # Add to the list
      model_summaries_list <- append(model_summaries_list, list(mplus_model_summaries))
    }
  }, silent = TRUE)  # Suppress errors and continue with the next file
}

# Check if summaries were successfully extracted
if (length(model_summaries_list) == 0) {
  stop("No model summaries were extracted. Please check the input files.")
}

# Standardize the columns of each summary
model_summaries_list <- lapply(model_summaries_list, function(summary) {
  # Add missing columns as NA
  missing_cols <- setdiff(all_columns, colnames(summary))
  for (col in missing_cols) {
    summary[[col]] <- NA
  }
  # Ensure columns are in the correct order
  summary <- summary[, all_columns, drop = FALSE]
  return(summary)
})

# Combine the summaries into a single data frame
all_summaries <- do.call(rbind, model_summaries_list)

# Create a new workbook
wb <- createWorkbook()

# Add a worksheet to the workbook
addWorksheet(wb, "Model Summaries")

# Write the combined model summaries to the worksheet
writeData(wb, sheet = 1, all_summaries)

#####USER CHANGE FOLDER HERE######
# Save the workbook to the specified folder
saveWorkbook(wb, "C:/Users/Jane Smith/Combined_model_summaries.xlsx", overwrite = TRUE)