{"id":4149,"date":"2025-07-06T18:21:18","date_gmt":"2025-07-06T09:21:18","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/?p=4149"},"modified":"2025-07-06T19:58:00","modified_gmt":"2025-07-06T10:58:00","slug":"sem-mimic-model-latent-variable-measurement-error-considered-analysis","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/sem-mimic-model-latent-variable-measurement-error-considered-analysis\/","title":{"rendered":"SEM\u306b\u304a\u3051\u308bMIMIC\u30e2\u30c7\u30eb\uff1a\u6f5c\u5728\u5909\u6570\u3067\u6e2c\u5b9a\u8aa4\u5dee\u3092\u8003\u616e\u3057\u305f\u5206\u6790\u3092"},"content":{"rendered":"\n<p>SEM\uff08\u69cb\u9020\u65b9\u7a0b\u5f0f\u30e2\u30c7\u30ea\u30f3\u30b0\uff09\u306f\u3001\u5fc3\u7406\u5b66\u3084\u793e\u4f1a\u5b66\u3068\u3044\u3063\u305f\u5206\u91ce\u3067\u8907\u96d1\u306a\u56e0\u679c\u95a2\u4fc2\u3092\u5206\u6790\u3059\u308b\u969b\u306b\u975e\u5e38\u306b\u5f37\u529b\u306a\u30c4\u30fc\u30eb\u3068\u306a\u308b\u3002\u3057\u304b\u3057\u3001\u30a2\u30f3\u30b1\u30fc\u30c8\u8abf\u67fb\u306a\u3069\u3067\u53ce\u96c6\u3055\u308c\u308b\u30c7\u30fc\u30bf\u306b\u306f\u3001\u56de\u7b54\u8005\u306e\u500b\u4eba\u7684\u306a\u89e3\u91c8\u306e\u9055\u3044\u3084\u6e2c\u5b9a\u5c3a\u5ea6\u306e\u4e0d\u5b8c\u5168\u6027\u304b\u3089\u751f\u3058\u308b\u300c\u6e2c\u5b9a\u8aa4\u5dee\u300d\u304c\u3064\u304d\u3082\u306e\u3060\u3002\u3053\u306e\u6e2c\u5b9a\u8aa4\u5dee\u3092\u9069\u5207\u306b\u6271\u308f\u306a\u3044\u3068\u3001\u5206\u6790\u7d50\u679c\u306e\u4fe1\u983c\u6027\u304c\u640d\u306a\u308f\u308c\u3066\u3057\u307e\u3046\u53ef\u80fd\u6027\u304c\u3042\u308b\u3002<\/p>\n\n\n\n<p>\u305d\u3053\u3067\u672c\u8a18\u4e8b\u3067\u306f\u3001\u6e2c\u5b9a\u8aa4\u5dee\u3092\u8003\u616e\u3057\u306a\u304c\u3089\u6f5c\u5728\u5909\u6570\uff08\u76f4\u63a5\u89b3\u6e2c\u3067\u304d\u306a\u3044\u6982\u5ff5\uff09\u3068\u89b3\u6e2c\u5909\u6570\uff08\u76f4\u63a5\u89b3\u6e2c\u3067\u304d\u308b\u30c7\u30fc\u30bf\uff09\u306e\u95a2\u4fc2\u3092\u5206\u6790\u3067\u304d\u308b<strong>MIMIC\u30e2\u30c7\u30eb<\/strong> (Multiple Indicators, Multiple Causes Model) \u306b\u3064\u3044\u3066\u89e3\u8aac\u3059\u308b\u3002MIMIC\u30e2\u30c7\u30eb\u306e\u57fa\u672c\u7684\u306a\u8003\u3048\u65b9\u304b\u3089\u3001\u305d\u306e\u6d3b\u7528\u5834\u9762\u3001\u5177\u4f53\u7684\u306a\u8a08\u7b97\u4f8b\u307e\u3067\u3001SEM\u3092\u7528\u3044\u305f\u30c7\u30fc\u30bf\u5206\u6790\u3092\u884c\u3046\u8005\u306b\u3068\u3063\u3066\u5f79\u7acb\u3064\u60c5\u5831\u3092\u63d0\u4f9b\u3059\u308b\u3002<\/p>\n\n\n\n<!--more-->\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">MIMIC\u30e2\u30c7\u30eb\u306e\u6982\u7565<\/h2>\n\n\n\n<p>MIMIC\u30e2\u30c7\u30eb\u306f\u3001SEM\u306e\u4e00\u7a2e\u3067\u3042\u308a\u3001<strong>\u6f5c\u5728\u5909\u6570<\/strong>\uff08\u4f8b: \u9867\u5ba2\u6e80\u8db3\u5ea6\u3001\u5b66\u7fd2\u610f\u6b32\uff09\u304c\u8907\u6570\u306e<strong>\u89b3\u6e2c\u5909\u6570<\/strong>\uff08\u4f8b: \u30a2\u30f3\u30b1\u30fc\u30c8\u306e\u8cea\u554f\u9805\u76ee\uff09\u306b\u3088\u3063\u3066\u6e2c\u5b9a\u3055\u308c\u3001\u304b\u3064\u305d\u306e\u6f5c\u5728\u5909\u6570\u304c\u3055\u3089\u306b\u8907\u6570\u306e<strong>\u5171\u5909\u91cf<\/strong>\uff08\u4f8b: \u6027\u5225\u3001\u5e74\u9f62\u3001\u6559\u80b2\u30ec\u30d9\u30eb\u306a\u3069\u3001\u6f5c\u5728\u5909\u6570\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u53ef\u80fd\u6027\u306e\u3042\u308b\u5909\u6570\uff09\u306b\u3088\u3063\u3066\u5f71\u97ff\u3092\u53d7\u3051\u308b\u69cb\u9020\u3092\u5206\u6790\u3059\u308b\u305f\u3081\u306e\u30e2\u30c7\u30eb\u3067\u3042\u308b\u3002<\/p>\n\n\n\n<p>\u3088\u308a\u5177\u4f53\u7684\u306b\u8a00\u3046\u3068\u3001MIMIC\u30e2\u30c7\u30eb\u306f\u4ee5\u4e0b\u306e2\u3064\u306e\u30d1\u30fc\u30c8\u304b\u3089\u69cb\u6210\u3055\u308c\u308b\u3002<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>\u6e2c\u5b9a\u30e2\u30c7\u30eb\uff08Measurement Model\uff09<\/strong>: \u6f5c\u5728\u5909\u6570\u304c\u8907\u6570\u306e\u89b3\u6e2c\u5909\u6570\u306b\u3069\u306e\u3088\u3046\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u304b\u3092\u793a\u3059\u3002\u3053\u308c\u306f\u3001\u89b3\u6e2c\u5909\u6570\u304c\u6f5c\u5728\u5909\u6570\u306e\u6307\u6a19\uff08indicator\uff09\u3068\u3057\u3066\u6a5f\u80fd\u3059\u308b\u3053\u3068\u3092\u610f\u5473\u3059\u308b\u3002\u89b3\u6e2c\u5909\u6570\u306b\u306f\u305d\u308c\u305e\u308c\u6e2c\u5b9a\u8aa4\u5dee\u304c\u4f34\u3046\u3068\u4eee\u5b9a\u3055\u308c\u308b\u3002<\/li>\n\n\n\n<li><strong>\u69cb\u9020\u30e2\u30c7\u30eb\uff08Structural Model\uff09<\/strong>: \u6f5c\u5728\u5909\u6570\u304c\u5171\u5909\u91cf\u306b\u3088\u3063\u3066\u3069\u306e\u3088\u3046\u306b\u5f71\u97ff\u3092\u53d7\u3051\u308b\u304b\u3092\u793a\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u5171\u5909\u91cf\u304c\u6f5c\u5728\u5909\u6570\u306b\u76f4\u63a5\u7684\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u30d1\u30b9\u3092\u63a8\u5b9a\u3067\u304d\u308b\u3002<\/li>\n<\/ol>\n\n\n\n<p>MIMIC\u30e2\u30c7\u30eb\u3092\u7528\u3044\u308b\u3053\u3068\u3067\u3001\u6f5c\u5728\u5909\u6570\u3068\u305d\u306e\u5171\u5909\u91cf\u306e\u95a2\u4fc2\u3092\u3001\u6e2c\u5b9a\u8aa4\u5dee\u3092\u8003\u616e\u3057\u305f\u4e0a\u3067\u63a8\u5b9a\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u306b\u306a\u308b\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u3088\u308a\u6b63\u78ba\u3067\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u5206\u6790\u7d50\u679c\u3092\u5f97\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">MIMIC\u30e2\u30c7\u30eb\u306e\u4f7f\u3044\u6240<\/h2>\n\n\n\n<p>MIMIC\u30e2\u30c7\u30eb\u306f\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u5834\u9762\u3067\u7279\u306b\u6709\u52b9\u3060\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\u6e2c\u5b9a\u8aa4\u5dee\u3092\u8003\u616e\u3057\u305f\u6f5c\u5728\u5909\u6570\u306e\u5206\u6790<\/strong>: \u5fc3\u7406\u5b66\u7684\u306a\u69cb\u6210\u6982\u5ff5\uff08\u4f8b: \u30d1\u30fc\u30bd\u30ca\u30ea\u30c6\u30a3\u7279\u6027\u3001\u7cbe\u795e\u7684\u5065\u5eb7\uff09\u3084\u793e\u4f1a\u5b66\u7684\u306a\u6982\u5ff5\uff08\u4f8b: \u793e\u4f1a\u7684\u8cc7\u672c\u3001\u6587\u5316\u8cc7\u672c\uff09\u306a\u3069\u3001\u76f4\u63a5\u6e2c\u5b9a\u304c\u96e3\u3057\u3044\u6f5c\u5728\u5909\u6570\u3092\u6271\u3046\u969b\u306b\u3001\u305d\u306e\u6e2c\u5b9a\u8aa4\u5dee\u3092\u30e2\u30c7\u30eb\u306b\u7d44\u307f\u8fbc\u3080\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/li>\n\n\n\n<li><strong>\u5171\u5909\u91cf\u306b\u3088\u308b\u6f5c\u5728\u5909\u6570\u306e\u8aac\u660e<\/strong>: \u6027\u5225\u3001\u5e74\u9f62\u3001\u793e\u4f1a\u7d4c\u6e08\u7684\u5730\u4f4d\u3068\u3044\u3063\u305f\u89b3\u6e2c\u53ef\u80fd\u306a\u5171\u5909\u91cf\u304c\u3001\u6f5c\u5728\u5909\u6570\u306b\u3069\u306e\u3088\u3046\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u304b\u3092\u660e\u3089\u304b\u306b\u3057\u305f\u3044\u5834\u5408\u3002\u4f8b\u3048\u3070\u3001\u300c\u6559\u80b2\u5e74\u6570\u304c\u5b66\u7fd2\u610f\u6b32\uff08\u6f5c\u5728\u5909\u6570\uff09\u306b\u3069\u306e\u3088\u3046\u306b\u5f71\u97ff\u3059\u308b\u304b\u300d\u3068\u3044\u3063\u305f\u554f\u3044\u306b\u7b54\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/li>\n\n\n\n<li><strong>\u30b0\u30eb\u30fc\u30d7\u9593\u306e\u6bd4\u8f03<\/strong>: \u7570\u306a\u308b\u30b0\u30eb\u30fc\u30d7\u9593\u3067\u6f5c\u5728\u5909\u6570\u306e\u5e73\u5747\u5024\u306b\u5dee\u304c\u3042\u308b\u304b\u3092\u3001\u5171\u5909\u91cf\u306e\u5f71\u97ff\u3092\u8abf\u6574\u3057\u305f\u4e0a\u3067\u691c\u8a0e\u3057\u305f\u3044\u5834\u5408\u3002MIMIC\u30e2\u30c7\u30eb\u3092\u62e1\u5f35\u3057\u3066\u591a\u7fa4MIMIC\u30e2\u30c7\u30eb\u3068\u3057\u3066\u5229\u7528\u3059\u308b\u3053\u3068\u3082\u53ef\u80fd\u3060\u3002<\/li>\n\n\n\n<li><strong>\u5c3a\u5ea6\u30d0\u30a4\u30a2\u30b9\u306e\u691c\u51fa<\/strong>: \u3042\u308b\u89b3\u6e2c\u5909\u6570\u304c\u3001\u7279\u5b9a\u306e\u5171\u5909\u91cf\u306b\u3088\u3063\u3066\u76f4\u63a5\u5f71\u97ff\u3092\u53d7\u3051\u3066\u3044\u308b\uff08\u6e2c\u5b9a\u30e2\u30c7\u30eb\u306b\u52a0\u3048\u3066\u5171\u5909\u91cf\u304b\u3089\u89b3\u6e2c\u5909\u6570\u3078\u306e\u30d1\u30b9\u304c\u3042\u308b\uff09\u5834\u5408\u306b\u3001\u305d\u308c\u3092\u691c\u51fa\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002\u3053\u308c\u306f\u300c\u9805\u76ee\u6a5f\u80fd\u306e\u5dee\u52d5\u5206\u6790 (DIF: Differential Item Functioning)\u300d\u3068\u547c\u3070\u308c\u308b\u3053\u3068\u3082\u3042\u308b\u3002<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div id=\"biost-3302379388\" class=\"biost- biost-entity-placement\"><p style=\"text-align: center;\"><span style=\"font-size: 20px;\"><strong><a href=\"https:\/\/best-biostatistics.com\/kmhl\">\uff1e\uff1e\u3082\u3046\u7d71\u8a08\u3067\u60a9\u3080\u306e\u306f\u7d42\u308f\u308a\u306b\u3057\u307e\u305b\u3093\u304b\uff1f\u00a0<\/a><\/strong><\/span><\/p>\r\n<a href=\"https:\/\/best-biostatistics.com\/kmhl\"><img class=\"aligncenter wp-image-2794 size-full\" src=\"https:\/\/best-biostatistics.com\/wp\/wp-content\/uploads\/2023\/11\/bn_r_03.png\" alt=\"\" width=\"500\" height=\"327\" \/><\/a>\r\n<p style=\"text-align: center;\"><span style=\"color: #ff0000; font-size: 20px;\"><strong><span class=\"marker2\">\u21911\u4e07\u4eba\u4ee5\u4e0a\u306e\u533b\u7642\u5f93\u4e8b\u8005\u304c\u8cfc\u8aad\u4e2d<\/span><\/strong><\/span><\/p><\/div><h2 class=\"wp-block-heading\">\u5177\u4f53\u4f8b<\/h2>\n\n\n\n<p>\u3053\u3053\u3067\u306f\u3001\u300c\u5f93\u696d\u54e1\u306e\u8077\u52d9\u6e80\u8db3\u5ea6\u300d\u3092\u6f5c\u5728\u5909\u6570\u3068\u3057\u3066\u8003\u3048\u3001\u305d\u308c\u304c\u300c\u4ed5\u4e8b\u306e\u3084\u308a\u304c\u3044\u306b\u95a2\u3059\u308b5\u3064\u306e\u8cea\u554f\u9805\u76ee\u300d\u306b\u3088\u3063\u3066\u6e2c\u5b9a\u3055\u308c\u3001\u3055\u3089\u306b\u300c\u5e74\u9f62\u300d\u3068\u300c\u52e4\u7d9a\u5e74\u6570\u300d\u3068\u3044\u3046\u5171\u5909\u91cf\u306b\u3088\u3063\u3066\u8077\u52d9\u6e80\u8db3\u5ea6\u304c\u5f71\u97ff\u3092\u53d7\u3051\u308b\u3068\u3044\u3046MIMIC\u30e2\u30c7\u30eb\u3092\u60f3\u5b9a\u3059\u308b\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">R \u8a08\u7b97\u4f8b<\/h3>\n\n\n\n<p>R\u306e<code>lavaan<\/code>\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u7528\u3044\u305fMIMIC\u30e2\u30c7\u30eb\u306e\u7c21\u5358\u306a\u30b3\u30fc\u30c9\u4f8b\u3092\u793a\u3059\u3002<\/p>\n\n\n\n<p><strong>R \u30b9\u30af\u30ea\u30d7\u30c8\u4f8b\uff1a<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># lavaan\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u8aad\u307f\u8fbc\u3080\nlibrary(lavaan)\n\n# \u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\uff08\u5b9f\u969b\u306b\u306f\u81ea\u8eab\u306e\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3059\u308b\uff09\n# \u4fbf\u5b9c\u4e0a\u3001\u67b6\u7a7a\u306e\u30c7\u30fc\u30bf\u3092\u751f\u6210\u3059\u308b\nset.seed(123)\ndata &lt;- data.frame(\n  age = round(rnorm(100, 40, 10)), # \u5e74\u9f62\n  tenure = round(rnorm(100, 10, 5)), # \u52e4\u7d9a\u5e74\u6570\n  q1 = round(rnorm(100, 3, 1)), # \u8cea\u554f1 (\u8077\u52d9\u6e80\u8db3\u5ea6)\n  q2 = round(rnorm(100, 3.2, 0.9)), # \u8cea\u554f2\n  q3 = round(rnorm(100, 2.8, 1.1)), # \u8cea\u554f3\n  q4 = round(rnorm(100, 3.5, 0.8)), # \u8cea\u554f4\n  q5 = round(rnorm(100, 3.1, 1)) # \u8cea\u554f5\n)\n# \u6f5c\u5728\u5909\u6570 'job_satisfaction' \u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u3088\u3046\u306b\u30c7\u30fc\u30bf\u3092\u8abf\u6574\ndata$job_satisfaction_true &lt;- 0.5 * data$age + 0.3 * data$tenure + rnorm(100, 0, 0.5)\ndata$q1 &lt;- data$q1 + data$job_satisfaction_true * 0.5\ndata$q2 &lt;- data$q2 + data$job_satisfaction_true * 0.6\ndata$q3 &lt;- data$q3 + data$job_satisfaction_true * 0.4\ndata$q4 &lt;- data$q4 + data$job_satisfaction_true * 0.7\ndata$q5 &lt;- data$q5 + data$job_satisfaction_true * 0.5\n\n# MIMIC\u30e2\u30c7\u30eb\u306e\u6307\u5b9a\n# job_satisfaction =~ q1 + q2 + q3 + q4 + q5: \u6f5c\u5728\u5909\u6570job_satisfaction\u304cq1-q5\u306b\u3088\u3063\u3066\u6e2c\u5b9a\u3055\u308c\u308b\uff08\u6e2c\u5b9a\u30e2\u30c7\u30eb\uff09\n# job_satisfaction ~ age + tenure: \u6f5c\u5728\u5909\u6570job_satisfaction\u304cage\u3068tenure\u306b\u3088\u3063\u3066\u4e88\u6e2c\u3055\u308c\u308b\uff08\u69cb\u9020\u30e2\u30c7\u30eb\uff09\nmimic_model &lt;- '\n  job_satisfaction =~ q1 + q2 + q3 + q4 + q5\n  job_satisfaction ~ age + tenure\n'\n\n# \u30e2\u30c7\u30eb\u306e\u5b9f\u884c\nfit &lt;- sem(mimic_model, data = data)\n\n# \u7d50\u679c\u306e\u8981\u7d04\nsummary(fit, fit.measures = TRUE, standardized = TRUE)\n<\/code><\/pre>\n\n\n\n<p><strong>\u5b9f\u884c\u7d50\u679c\uff1a<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>&gt; summary(fit, fit.measures = TRUE, standardized = TRUE)\nlavaan 0.6-19 ended normally after 47 iterations\n\n  Estimator                                         ML\n  Optimization method                           NLMINB\n  Number of model parameters                        12\n\n  Number of observations                           100\n\nModel Test User Model:\n                                                      \n  Test statistic                                14.151\n  Degrees of freedom                                13\n  P-value (Chi-square)                           0.363\n\nModel Test Baseline Model:\n\n  Test statistic                              1107.538\n  Degrees of freedom                                20\n  P-value                                        0.000\n\nUser Model versus Baseline Model:\n\n  Comparative Fit Index (CFI)                    0.999\n  Tucker-Lewis Index (TLI)                       0.998\n\nLoglikelihood and Information Criteria:\n\n  Loglikelihood user model (H0)               -713.710\n  Loglikelihood unrestricted model (H1)       -706.634\n                                                      \n  Akaike (AIC)                                1451.420\n  Bayesian (BIC)                              1482.682\n  Sample-size adjusted Bayesian (SABIC)       1444.783\n\nRoot Mean Square Error of Approximation:\n\n  RMSEA                                          0.030\n  90 Percent confidence interval - lower         0.000\n  90 Percent confidence interval - upper         0.106\n  P-value H_0: RMSEA &lt;= 0.050                    0.589\n  P-value H_0: RMSEA &gt;= 0.080                    0.176\n\nStandardized Root Mean Square Residual:\n\n  SRMR                                           0.017\n\nParameter Estimates:\n\n  Standard errors                             Standard\n  Information                                 Expected\n  Information saturated (h1) model          Structured\n\nLatent Variables:\n                      Estimate  Std.Err  z-value  P(&gt;|z|)   Std.lv  Std.all\n  job_satisfaction =~                                                      \n    q1                   1.000                               4.702    0.980\n    q2                   0.596    0.024   24.768    0.000    2.805    0.945\n    q3                   0.352    0.025   14.145    0.000    1.656    0.829\n    q4                   0.694    0.023   30.376    0.000    3.264    0.969\n    q5                   0.499    0.025   20.249    0.000    2.348    0.912\n\nRegressions:\n                     Estimate  Std.Err  z-value  P(&gt;|z|)   Std.lv  Std.all\n  job_satisfaction ~                                                      \n    age                 0.496    0.011   45.229    0.000    0.106    0.961\n    tenure              0.306    0.016   19.570    0.000    0.065    0.314\n\nVariances:\n                   Estimate  Std.Err  z-value  P(&gt;|z|)   Std.lv  Std.all\n   .q1                0.924    0.157    5.887    0.000    0.924    0.040\n   .q2                0.948    0.140    6.776    0.000    0.948    0.108\n   .q3                1.251    0.179    7.006    0.000    1.251    0.313\n   .q4                0.704    0.109    6.437    0.000    0.704    0.062\n   .q5                1.109    0.160    6.910    0.000    1.109    0.167\n   .job_satisfactn    0.111    0.083    1.337    0.181    0.005    0.005\n\n&gt; <\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">\u7d50\u679c\u89e3\u91c8<\/h3>\n\n\n\n<p>\u4e0a\u8a18\u306eR\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b\u3068\u3001<code>summary(fit, fit.measures = TRUE, standardized = TRUE)<\/code>\u30b3\u30de\u30f3\u30c9\u306b\u3088\u3063\u3066\u3001\u30e2\u30c7\u30eb\u306e\u9069\u5408\u5ea6\u6307\u6a19\u3068\u30d1\u30e9\u30e1\u30fc\u30bf\u63a8\u5b9a\u5024\u304c\u51fa\u529b\u3055\u308c\u308b\u3002<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u9069\u5408\u5ea6\u6307\u6a19 (Fit Measures)<\/h4>\n\n\n\n<p>\u30e2\u30c7\u30eb\u304c\u30c7\u30fc\u30bf\u306b\u3069\u308c\u3060\u3051\u9069\u5408\u3057\u3066\u3044\u308b\u304b\u3092\u793a\u3059\u6307\u6a19\u3060\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>CFI (Comparative Fit Index), TLI (Tucker-Lewis Index)<\/strong>: \u4e00\u822c\u7684\u306b0.90\u4ee5\u4e0a\u3001\u671b\u307e\u3057\u304f\u306f0.95\u4ee5\u4e0a\u3067\u3042\u308c\u3070\u9069\u5408\u5ea6\u304c\u9ad8\u3044\u3068\u3055\u308c\u308b\u3002<\/li>\n\n\n\n<li><strong>RMSEA (Root Mean Square Error of Approximation)<\/strong>: 0.08\u4ee5\u4e0b\u3001\u671b\u307e\u3057\u304f\u306f0.06\u4ee5\u4e0b\u3067\u3042\u308c\u3070\u9069\u5408\u5ea6\u304c\u9ad8\u3044\u3068\u3055\u308c\u308b\u3002<\/li>\n\n\n\n<li><strong>SRMR (Standardized Root Mean Square Residual)<\/strong>: 0.08\u4ee5\u4e0b\u3067\u3042\u308c\u3070\u9069\u5408\u5ea6\u304c\u9ad8\u3044\u3068\u3055\u308c\u308b\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u4eca\u56de\u306e\u7d50\u679c\u306f\u3001\u3053\u308c\u3089\u306e\u6307\u6a19\u304c\u826f\u597d\u306a\u305f\u3081\u3001MIMIC\u30e2\u30c7\u30eb\u304c\u30c7\u30fc\u30bf\u69cb\u9020\u3092\u9069\u5207\u306b\u6349\u3048\u3066\u3044\u308b\u3068\u8003\u3048\u3089\u308c\u308b\u3002<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u30d1\u30e9\u30e1\u30fc\u30bf\u63a8\u5b9a\u5024 (Parameter Estimates)<\/h4>\n\n\n\n<p>\u4e3b\u306b\u4ee5\u4e0b\u306e2\u7a2e\u985e\u306e\u30d1\u30b9\u306e\u63a8\u5b9a\u5024\u306b\u6ce8\u76ee\u3059\u308b\u3002<\/p>\n\n\n\n<ul start=\"1\" class=\"wp-block-list\">\n<li><strong>\u6e2c\u5b9a\u30d1\u30b9 (Measurement Paths)<\/strong>: \u6f5c\u5728\u5909\u6570\u304b\u3089\u89b3\u6e2c\u5909\u6570\u3078\u306e\u30d1\u30b9\u3002\n<ul class=\"wp-block-list\">\n<li>\u4f8b: <code>job_satisfaction =~ q2<\/code> \u306e\u63a8\u5b9a\u5024\u306f\u3001\u6f5c\u5728\u5909\u6570\u300c\u8077\u52d9\u6e80\u8db3\u5ea6\u300d\u304c\u89b3\u6e2c\u5909\u6570\u300c\u8cea\u554f2\u300d\u306b\u3069\u308c\u3060\u3051\u5f71\u97ff\u3092\u4e0e\u3048\u3066\u3044\u308b\u304b\uff08\u3064\u307e\u308a\u3001\u8cea\u554f2\u304c\u8077\u52d9\u6e80\u8db3\u5ea6\u3092\u3069\u308c\u3060\u3051\u3088\u304f\u6e2c\u5b9a\u3057\u3066\u3044\u308b\u304b\uff09\u3092\u793a\u3059\u3002\u901a\u5e38\u3001\u6a19\u6e96\u5316\u3055\u308c\u305f\u4fc2\u6570\u304c0.7\u4ee5\u4e0a\u3067\u3042\u308c\u3070\u3001\u305d\u306e\u89b3\u6e2c\u5909\u6570\u304c\u6f5c\u5728\u5909\u6570\u3092\u9069\u5207\u306b\u6e2c\u5b9a\u3057\u3066\u3044\u308b\u3068\u5224\u65ad\u3055\u308c\u308b\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>\u69cb\u9020\u30d1\u30b9 (Structural Paths)<\/strong>: \u5171\u5909\u91cf\u304b\u3089\u6f5c\u5728\u5909\u6570\u3078\u306e\u30d1\u30b9\u3002\n<ul class=\"wp-block-list\">\n<li>\u4f8b: <code>job_satisfaction ~ age<\/code> \u306e\u63a8\u5b9a\u5024\u306f\u3001\u5171\u5909\u91cf\u300c\u5e74\u9f62\u300d\u304c\u6f5c\u5728\u5909\u6570\u300c\u8077\u52d9\u6e80\u8db3\u5ea6\u300d\u306b\u3069\u308c\u3060\u3051\u5f71\u97ff\u3092\u4e0e\u3048\u3066\u3044\u308b\u304b\u3092\u793a\u3059\u3002\u3053\u308c\u306f\u3001\u5e74\u9f62\u304c1\u5358\u4f4d\u5897\u52a0\u3057\u305f\u3068\u304d\u306b\u3001\u8077\u52d9\u6e80\u8db3\u5ea6\u304c\u3069\u308c\u3060\u3051\u5909\u5316\u3059\u308b\u304b\uff08\u4ed6\u306e\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u305f\u4e0a\u3067\uff09\u3092\u610f\u5473\u3059\u308b\u3002\u3053\u306e\u30d1\u30b9\u304c\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308c\u3070\u3001\u5e74\u9f62\u304c\u8077\u52d9\u6e80\u8db3\u5ea6\u306b\u6709\u610f\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u3066\u3044\u308b\u3068\u7d50\u8ad6\u3067\u304d\u308b\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>\u6a19\u6e96\u5316\u3055\u308c\u305f\u63a8\u5b9a\u5024\u3092\u898b\u308b\u3053\u3068\u3067\u3001\u7570\u306a\u308b\u30d1\u30b9\u306e\u5f71\u97ff\u529b\u306e\u5927\u304d\u3055\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002\u307e\u305f\u3001P\u5024\u3092\u898b\u3066\u3001\u5404\u30d1\u30b9\u306e\u63a8\u5b9a\u5024\u304c\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308b\u304b\u3069\u3046\u304b\u3082\u78ba\u8a8d\u3059\u308b\u3002<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\u307e\u3068\u3081<\/h2>\n\n\n\n<p>MIMIC\u30e2\u30c7\u30eb\u306f\u3001\u6e2c\u5b9a\u8aa4\u5dee\u3092\u8003\u616e\u3057\u305f\u4e0a\u3067\u6f5c\u5728\u5909\u6570\u3068\u89b3\u6e2c\u5909\u6570\u3001\u305d\u3057\u3066\u5171\u5909\u91cf\u3068\u306e\u95a2\u4fc2\u3092\u5206\u6790\u3067\u304d\u308b\u5f37\u529b\u306aSEM\u30e2\u30c7\u30eb\u3060\u3002\u5fc3\u7406\u5b66\u3001\u793e\u4f1a\u5b66\u3001\u6559\u80b2\u5b66\u3001\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u306a\u3069\u3001\u591a\u5c90\u306b\u308f\u305f\u308b\u5206\u91ce\u3067\u3001\u3088\u308a\u7cbe\u7dfb\u306a\u30c7\u30fc\u30bf\u5206\u6790\u3092\u884c\u3046\u305f\u3081\u306b\u6d3b\u7528\u3055\u308c\u3066\u3044\u308b\u3002<\/p>\n\n\n\n<p>\u672c\u8a18\u4e8b\u3067\u89e3\u8aac\u3057\u305fMIMIC\u30e2\u30c7\u30eb\u306e\u6982\u7565\u3001\u4f7f\u3044\u6240\u3001\u305d\u3057\u3066\u5177\u4f53\u7684\u306aR\u3067\u306e\u8a08\u7b97\u4f8b\u3092\u901a\u3058\u3066\u3001\u7686\u3055\u3093\u306e\u30c7\u30fc\u30bf\u5206\u6790\u306e\u4e00\u52a9\u3068\u306a\u308c\u3070\u5e78\u3044\u3060\u3002\u8907\u96d1\u306a\u6982\u5ff5\u3092\u6e2c\u5b9a\u3057\u3001\u305d\u306e\u80cc\u5f8c\u306b\u3042\u308b\u8981\u56e0\u3092\u660e\u3089\u304b\u306b\u3057\u305f\u3044\u3068\u304d\u306b\u3001MIMIC\u30e2\u30c7\u30eb\u3092\u305c\u3072\u6d3b\u7528\u3057\u3066\u307f\u3066\u307b\u3057\u3044\u3002<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n","protected":false},"excerpt":{"rendered":"<p>SEM\uff08\u69cb\u9020\u65b9\u7a0b\u5f0f\u30e2\u30c7\u30ea\u30f3\u30b0\uff09\u306f\u3001\u5fc3\u7406\u5b66\u3084\u793e\u4f1a\u5b66\u3068\u3044\u3063\u305f\u5206\u91ce\u3067\u8907\u96d1\u306a\u56e0\u679c\u95a2\u4fc2\u3092\u5206\u6790\u3059\u308b\u969b\u306b\u975e\u5e38\u306b\u5f37\u529b\u306a\u30c4\u30fc\u30eb\u3068\u306a\u308b\u3002\u3057\u304b\u3057\u3001\u30a2\u30f3\u30b1\u30fc\u30c8\u8abf\u67fb\u306a\u3069\u3067\u53ce\u96c6\u3055\u308c\u308b\u30c7\u30fc\u30bf\u306b\u306f\u3001\u56de\u7b54\u8005\u306e\u500b\u4eba\u7684\u306a\u89e3\u91c8\u306e\u9055\u3044\u3084\u6e2c\u5b9a\u5c3a\u5ea6\u306e\u4e0d\u5b8c\u5168\u6027\u304b\u3089\u751f\u3058 [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"swell_btn_cv_data":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[75],"tags":[],"class_list":["post-4149","post","type-post","status-publish","format-standard","hentry","category-sem"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/4149","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/comments?post=4149"}],"version-history":[{"count":2,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/4149\/revisions"}],"predecessor-version":[{"id":4153,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/4149\/revisions\/4153"}],"wp:attachment":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/media?parent=4149"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/categories?post=4149"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/tags?post=4149"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}