176 lines
7.8 KiB
R
176 lines
7.8 KiB
R
setwd("C:/Users/irina/Documents/DND/EOHI/eohi2")
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options(scipen = 999)
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df <- read.csv("eohi2.csv")
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library(psych)
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library(dplyr)
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library(knitr)
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# Your named variable sets (replace df with your actual dataframe name)
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present_pref_vars <- c("present_pref_read", "present_pref_music", "present_pref_tv", "present_pref_nap", "present_pref_travel")
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past_5_pref_vars <- c("past_5_pref_read", "past_5_pref_music", "past_5_pref_TV", "past_5_pref_nap", "past_5_pref_travel")
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past_10_pref_vars <- c("past_10_pref_read", "past_10_pref_music", "past_10_pref_TV", "past_10_pref_nap", "past_10_pref_travel")
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fut_5_pref_vars <- c("fut_5_pref_read", "fut_5_pref_music", "fut_5_pref_TV", "fut_5_pref_nap", "fut_5_pref_travel")
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fut_10_pref_vars <- c("fut_10_pref_read", "fut_10_pref_music", "fut_10_pref_TV", "fut_10_pref_nap", "fut_10_pref_travel")
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present_pers_vars <- c("present_pers_extravert", "present_pers_critical", "present_pers_dependable", "present_pers_anxious", "present_pers_complex")
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past_5_pers_vars <- c("past_5_pers_extravert", "past_5_pers_critical", "past_5_pers_dependable", "past_5_pers_anxious", "past_5_pers_complex")
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past_10_pers_vars <- c("past_10_pers_extravert", "past_10_pers_critical", "past_10_pers_dependable", "past_10_pers_anxious", "past_10_pers_complex")
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fut_5_pers_vars <- c("fut_5_pers_extravert", "fut_5_pers_critical", "fut_5_pers_dependable", "fut_5_pers_anxious", "fut_5_pers_complex")
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fut_10_pers_vars <- c("fut_10_pers_extravert", "fut_10_pers_critical", "fut_10_pers_dependable", "fut_10_pers_anxious", "fut_10_pers_complex")
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present_val_vars <- c("present_val_obey", "present_val_trad", "present_val_opinion", "present_val_performance", "present_val_justice")
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past_5_val_vars <- c("past_5_val_obey", "past_5_val_trad", "past_5_val_opinion", "past_5_val_performance", "past_5_val_justice")
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past_10_val_vars <- c("past_10_val_obey", "past_10_val_trad", "past_10_val_opinion", "past_10_val_performance", "past_10_val_justice")
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fut_5_val_vars <- c("fut_5_val_obey", "fut_5_val_trad", "fut_5_val_opinion", "fut_5_val_performance", "fut_5_val_justice")
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fut_10_val_vars <- c("fut_10_val_obey", "fut_10_val_trad", "fut_10_val_opinion", "fut_10_val_performance", "fut_10_val_justice")
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all_scales <- list(
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"Present_Preferences" = present_pref_vars,
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"Past5_Preferences" = past_5_pref_vars,
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"Past10_Preferences" = past_10_pref_vars,
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"Fut5_Preferences" = fut_5_pref_vars,
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"Fut10_Preferences" = fut_10_pref_vars,
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"Present_Personality" = present_pers_vars,
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"Past5_Personality" = past_5_pers_vars,
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"Past10_Personality" = past_10_pers_vars,
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"Fut5_Personality" = fut_5_pers_vars,
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"Fut10_Personality" = fut_10_pers_vars,
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"Present_Values" = present_val_vars,
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"Past5_Values" = past_5_val_vars,
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"Past10_Values" = past_10_val_vars,
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"Fut5_Values" = fut_5_val_vars,
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"Fut10_Values" = fut_10_val_vars
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)
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# Reliability analysis loop
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alpha_results <- list()
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total_results <- data.frame()
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item_stats_results <- data.frame()
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alpha_drop_results <- data.frame()
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for(scale_name in names(all_scales)) {
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vars <- all_scales[[scale_name]]
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scale_data <- df %>% select(all_of(vars))
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# Only run if there is more than one column present
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if(ncol(scale_data) > 1) {
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alpha_out <- psych::alpha(scale_data, check.keys = TRUE)
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alpha_results[[scale_name]] <- alpha_out
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# Print full output for diagnostics
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cat("\n----------", scale_name, "----------\n")
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print(alpha_out$total)
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print(alpha_out$item.stats)
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print(alpha_out$alpha.drop)
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# Prepare results for CSV export
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scale_total <- alpha_out$total
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scale_items <- alpha_out$item.stats
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scale_alpha_drop <- alpha_out$alpha.drop
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# Add scale name to each row
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scale_total$Scale <- scale_name
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scale_items$Scale <- scale_name
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scale_alpha_drop$Scale <- scale_name
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# Combine results by type
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total_results <- rbind(total_results, scale_total)
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item_stats_results <- rbind(item_stats_results, scale_items)
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alpha_drop_results <- rbind(alpha_drop_results, scale_alpha_drop)
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}
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}
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# Create HTML report
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html_content <- paste0("<!DOCTYPE html>
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<html>
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<head>
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<title>Reliability Analysis Results</title>
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<style>
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body { font-family: Arial, sans-serif; margin: 20px; }
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h1 { color: #2c3e50; }
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h2 { color: #34495e; border-bottom: 2px solid #3498db; padding-bottom: 5px; }
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table { border-collapse: collapse; width: 100%; margin: 20px 0; }
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th, td { border: 1px solid #ddd; padding: 8px; text-align: left; }
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th { background-color: #3498db; color: white; }
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tr:nth-child(even) { background-color: #f2f2f2; }
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.scale-section { margin: 30px 0; }
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.summary-stats { background-color: #ecf0f1; padding: 15px; border-radius: 5px; }
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</style>
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</head>
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<body>
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<h1>Reliability Analysis Results</h1>
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<p>Generated on: ", Sys.time(), "</p>")
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# Add total statistics
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html_content <- paste0(html_content, "<h2>Overall Scale Statistics</h2>
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<div class='summary-stats'>
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<table>
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<tr><th>Scale</th><th>Raw Alpha</th><th>Std Alpha</th><th>G6(SMC)</th><th>Average r</th><th>S/N</th><th>ASE</th><th>Mean</th><th>SD</th><th>Median r</th></tr>")
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for(i in 1:nrow(total_results)) {
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row <- total_results[i,]
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html_content <- paste0(html_content, sprintf("<tr><td>%s</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td></tr>",
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row$Scale, row$raw_alpha, row$std.alpha, row$G6.smc, row$average_r, row$S.N, row$ase, row$mean, row$sd, row$median_r))
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}
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html_content <- paste0(html_content, "</table></div>")
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# Add item statistics
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html_content <- paste0(html_content, "<h2>Item Statistics</h2>
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<table>
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<tr><th>Scale</th><th>Item</th><th>n</th><th>Raw r</th><th>Std r</th><th>r.cor</th><th>r.drop</th><th>Mean</th><th>SD</th></tr>")
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for(i in 1:nrow(item_stats_results)) {
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row <- item_stats_results[i,]
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html_content <- paste0(html_content, sprintf("<tr><td>%s</td><td>%s</td><td>%.0f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td></tr>",
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row$Scale, rownames(row), row$n, row$raw.r, row$std.r, row$r.cor, row$r.drop, row$mean, row$sd))
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}
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html_content <- paste0(html_content, "</table>")
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# Add alpha if dropped
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html_content <- paste0(html_content, "<h2>Alpha If Item Dropped</h2>
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<table>
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<tr><th>Scale</th><th>Item</th><th>Raw Alpha</th><th>Std Alpha</th><th>G6(SMC)</th><th>Average r</th><th>S/N</th><th>Alpha SE</th><th>Var r</th><th>Med r</th></tr>")
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for(i in 1:nrow(alpha_drop_results)) {
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row <- alpha_drop_results[i,]
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html_content <- paste0(html_content, sprintf("<tr><td>%s</td><td>%s</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td><td>%.4f</td></tr>",
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row$Scale, rownames(row), row$raw_alpha, row$std.alpha, row$G6.smc, row$average_r, row$S.N, row$alpha.se, row$var.r, row$med.r))
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}
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html_content <- paste0(html_content, "</table>
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</body>
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</html>")
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# Write HTML file
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writeLines(html_content, "reliability_analysis_report.html")
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# Check for reversed items
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cat("\n=== REVERSED ITEMS CHECK ===\n")
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for(scale_name in names(all_scales)) {
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vars <- all_scales[[scale_name]]
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scale_data <- df %>% select(all_of(vars))
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if(ncol(scale_data) > 1) {
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alpha_out <- alpha_results[[scale_name]]
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# Check if any items were reversed by looking at the keys
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if(!is.null(alpha_out$keys)) {
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keys_df <- as.data.frame(alpha_out$keys)
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reversed_items <- rownames(keys_df)[keys_df[,1] < 0]
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if(length(reversed_items) > 0) {
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cat(scale_name, "reversed items:", paste(reversed_items, collapse = ", "), "\n")
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} else {
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cat(scale_name, ": No items reversed\n")
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}
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} else {
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cat(scale_name, ": No keys available\n")
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}
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}
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}
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