{"id":687,"date":"2026-01-05T15:53:20","date_gmt":"2026-01-05T06:53:20","guid":{"rendered":"http:\/\/waurimal.kr\/?p=687"},"modified":"2026-01-05T15:53:22","modified_gmt":"2026-01-05T06:53:22","slug":"chap-38-%eb%b2%a0%ec%9d%b4%ec%a7%80%ec%95%88-%ea%b5%ac%ec%a1%b0%eb%b0%a9%ec%a0%95%ec%8b%9d-%eb%aa%a8%ed%98%95bayesian-structural-equation-modeling-bsem","status":"publish","type":"post","link":"http:\/\/waurimal.kr\/?p=687","title":{"rendered":"Chap 38. \ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM)"},"content":{"rendered":"\n<p>\uc548\ub155\ud558\uc138\uc694. \uc774\ubc88\uc5d0\ub294 \ud1b5\uacc4\ud559\uc758 \uc0c8\ub85c\uc6b4 \uc9c0\ud3c9\uc778 <strong>\ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM)<\/strong>\uc758 \uc138\uacc4\ub85c \ub4e4\uc5b4\uac00\ub294 \uac83\uc744 \ub3d5\uace0\uc790 \ud569\ub2c8\ub2e4. 2012\ub144 \ucd08\ud310 \uc774\ud6c4, \ubca0\uc774\uc9c0\uc548 \ucd94\ub860\uc740 \uc0ac\ud68c\uacfc\ud559 \ubc0f \ud589\ub3d9\uacfc\ud559 \ubd84\uc57c\uc5d0\uc11c \ube48\ub3c4\uc8fc\uc758(Frequentist) \ubc29\ubc95\ub860\uc758 \uac15\ub825\ud55c \ub300\uc548\uc73c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\ud2b9\ud788 \uc774\ubc88 \ub0b4\uc6a9\uc5d0\uc11c\ub294 <strong>Hamiltonian Monte Carlo (HMC)<\/strong> \uc54c\uace0\ub9ac\uc998\uacfc <strong>Stan<\/strong> \uac19\uc740 \uc624\ud508 \uc18c\uc2a4 \uc18c\ud504\ud2b8\uc6e8\uc5b4\uc758 \ubc1c\uc804\uc5d0 \ud798\uc785\uc5b4 \ub354\uc6b1 \uc815\uad50\ud574\uc9c4 BSEM\uc758 \uae30\ucd08\uc640 \ud655\uc7a5\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ub2e4\uc18c \ubcf5\uc7a1\ud560 \uc218 \uc788\ub294 \ub0b4\uc6a9\uc774\uc9c0\ub9cc, \ud559\uad50 \ud604\uc7a5\uc758 \uc608\uc2dc\ub97c \ud1b5\ud574 \uc54c\uae30 \uc27d\uac8c \ud480\uc5b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\ubd84\uc11d \ub3c4\uad6c\ub85c\ub294 \uc6b0\ub9ac\uac00 \uc218\uc5c5 \uc2dc\uac04\uc5d0 \uc790\uc8fc \ub2e4\ub8e8\ub294 <strong>jamovi<\/strong>\ub97c \uae30\ubcf8\uc73c\ub85c \ud558\ub418, \ubcf8\ubb38\uc5d0\uc11c \uac15\uc870\ud558\ub294 <code>blavaan<\/code> \ud328\ud0a4\uc9c0\uc758 \uace0\uae09 \uae30\ub2a5\uc744 \uad6c\ud604\ud558\uae30 \uc704\ud574 jamovi \ub0b4\uc758 <strong>Rj Editor<\/strong> (\ub610\ub294 R \ud658\uacbd)\ub97c \ud65c\uc6a9\ud558\ub294 \ucf54\ub4dc\ub97c \ud568\uaed8 \uc81c\uc2dc\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">1. \uc65c \ubca0\uc774\uc9c0\uc548\uc778\uac00?<\/h2>\n\n\n\n<p>\uc6b0\ub9ac\ub294 \uadf8\ub3d9\uc548 &#8220;p-value\uac00 .05\ubcf4\ub2e4 \uc791\uc740\uac00?&#8221;\uc5d0 \uc9d1\ucc29\ud574 \uc654\uc2b5\ub2c8\ub2e4. \ud558\uc9c0\ub9cc \ube48\ub3c4\uc8fc\uc758 \ud1b5\uacc4\ub294 &#8220;\ubaa8\uc218(parameter)\ub294 \uace0\uc815\ub418\uc5b4 \uc788\uace0 \ub370\uc774\ud130\uac00 \ud655\ub960\uc801&#8221;\uc774\ub77c\uace0 \ubd05\ub2c8\ub2e4. \ubc18\uba74, <strong>\ubca0\uc774\uc9c0\uc548 \ud1b5\uacc4<\/strong>\ub294 &#8220;\ub370\uc774\ud130\ub294 \uace0\uc815\ub418\uc5b4 \uc788\uace0, \ubaa8\uc218 \uc790\uccb4\uac00 \ud655\ub960 \ubd84\ud3ec\ub97c \uac00\uc9c4\ub2e4&#8221;\uace0 \ubd05\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\ubca0\uc774\uc9c0\uc548 \uc811\uadfc\uc758 \ud575\uc2ec \uc7a5\uc810\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>\ubd88\ud655\uc2e4\uc131\uc758 \uc815\ub7c9\ud654:<\/strong> \ubaa8\uc218 \ucd94\uc815\uce58 \uc8fc\ubcc0\uc758 \uad6c\uac04(\uc2e0\uc6a9\uad6c\uac04, Credible Interval)\uc774 \ube48\ub3c4\uc8fc\uc758\uc758 \uc2e0\ub8b0\uad6c\uac04\ubcf4\ub2e4 \ub354 \uc9c1\uad00\uc801\uc774\uace0 \uc194\uc9c1\ud569\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>\uc0ac\uc804 \uc815\ubcf4\uc758 \ud65c\uc6a9:<\/strong> \uc774\uc804 \uc5f0\uad6c \uacb0\uacfc\ub098 \uc804\ubb38\uac00\uc758 \uc758\uacac\uc744 &#8216;\uc0ac\uc804 \ubd84\ud3ec(Prior)&#8217;\ub85c \ubaa8\ud615\uc5d0 \ubc18\uc601\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>\ubcf5\uc7a1\ud55c \ubaa8\ud615 \ud574\uacb0:<\/strong> \ube48\ub3c4\uc8fc\uc758 \ubc29\uc2dd(\ucd5c\ub300\uc6b0\ub3c4\ubc95 \ub4f1)\uc73c\ub85c \uc218\ub834\ud558\uc9c0 \uc54a\ub294 \ubcf5\uc7a1\ud55c \ubaa8\ud615\ub3c4 MCMC \uc0d8\ud50c\ub9c1\uc744 \ud1b5\ud574 \ucd94\uc815\ud574 \ub0bc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">2. \ubca0\uc774\uc9c0\uc548 \ucd94\ub860\uc758 \ud575\uc2ec \uc694\uc18c<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">2.1 \ubca0\uc774\uc988 \uc815\ub9ac (Bayes&#8217; Theorem)<\/h3>\n\n\n\n<p>\ubca0\uc774\uc9c0\uc548 \ucd94\ub860\uc758 \uc2ec\uc7a5\uc740 \ub2e4\uc74c \uc2dd\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<p><math data-latex=\"p(\\theta|y) = \\frac{p(y|\\theta)p(\\theta)}{p(y)}\"><semantics><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>\u03b8<\/mi><mi>|<\/mi><mi>y<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><mo>=<\/mo><mfrac><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>y<\/mi><mi>|<\/mi><mi>\u03b8<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>\u03b8<\/mi><mo form=\"postfix\" stretchy=\"false\" lspace=\"0em\" rspace=\"0em\">)<\/mo><\/mrow><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>y<\/mi><mo form=\"postfix\" stretchy=\"false\" lspace=\"0em\" rspace=\"0em\">)<\/mo><\/mrow><\/mfrac><\/mrow><annotation encoding=\"application\/x-tex\">p(\\theta|y) = \\frac{p(y|\\theta)p(\\theta)}{p(y)}<\/annotation><\/semantics><\/math><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><math data-latex=\"p(\\theta|y)\"><semantics><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>\u03b8<\/mi><mi>|<\/mi><mi>y<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(\\theta|y)<\/annotation><\/semantics><\/math>: <strong>\uc0ac\ud6c4 \ubd84\ud3ec(Posterior)<\/strong>. \ub370\uc774\ud130\ub97c \uad00\uce21\ud55c \ud6c4\uc758 \ubaa8\uc218(\uc9c0\uc2dd).<\/li>\n\n\n\n<li><math data-latex=\"p(y|\\theta)\"><semantics><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>y<\/mi><mi>|<\/mi><mi>\u03b8<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(y|\\theta)<\/annotation><\/semantics><\/math>: <strong>\uc6b0\ub3c4(Likelihood)<\/strong>. \ub370\uc774\ud130\uac00 \uad00\uce21\ub420 \ud655\ub960(\ubaa8\ud615).<\/li>\n\n\n\n<li><math data-latex=\"p(\\theta)\"><semantics><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>\u03b8<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(\\theta)<\/annotation><\/semantics><\/math>: <strong>\uc0ac\uc804 \ubd84\ud3ec(Prior)<\/strong>. \ub370\uc774\ud130\ub97c \ubcf4\uae30 \uc804\uc758 \ubbff\uc74c.<\/li>\n\n\n\n<li><math data-latex=\"p(y)\"><semantics><mrow><mi>p<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mi>y<\/mi><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(y)<\/annotation><\/semantics><\/math>: \uc815\uaddc\ud654 \uc0c1\uc218.<\/li>\n<\/ul>\n\n\n\n<p>\uc989, <strong>&#8220;\uc0ac\ud6c4 \uc9c0\uc2dd = (\ub370\uc774\ud130\uc758 \uc99d\uac70 \u00d7 \uc0ac\uc804 \uc9c0\uc2dd) \/ \uc0c1\uc218&#8221;<\/strong> \uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2.2 \uc0ac\uc804 \ubd84\ud3ec(Prior)\uc758 \uc885\ub958<\/h3>\n\n\n\n<p>\uad50\uc721\ud559 \uc608\uc2dc\ub85c \uc124\uba85\ud574 \ubd05\uc2dc\ub2e4. &#8220;\uc601\uc7ac \ud559\uae09 \ud559\uc0dd\ub4e4\uc758 \ud3c9\uade0 IQ(<math data-latex=\"\\theta\"><semantics><mi>\u03b8<\/mi><annotation encoding=\"application\/x-tex\">\\theta<\/annotation><\/semantics><\/math>)&#8221;\ub97c \ucd94\uc815\ud55c\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>\ubb34\uc815\ubcf4 \uc0ac\uc804 \ubd84\ud3ec (Noninformative Prior):<\/strong> &#8220;\ub098\ub294 \uc544\ubb34\uac83\ub3c4 \ubaa8\ub978\ub2e4.&#8221;\n<ul class=\"wp-block-list\">\n<li>\uade0\ub4f1 \ubd84\ud3ec(Uniform Distribution) <math data-latex=\"U(0, 200)\"><semantics><mrow><mi>U<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mn>0<\/mn><mo separator=\"true\">,<\/mo><mn>200<\/mn><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">U(0, 200)<\/annotation><\/semantics><\/math> \ub4f1\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. 0\uc5d0\uc11c 200 \uc0ac\uc774\uc758 \ubaa8\ub4e0 \uac12\uc774 \ub3d9\ub4f1\ud55c \ud655\ub960\uc744 \uac00\uc9d1\ub2c8\ub2e4.<\/li>\n\n\n\n<li>\ub370\uc774\ud130\uac00 \uc2a4\uc2a4\ub85c \ub9d0\ud558\uac8c \ub0b4\ubc84\ub824 \ub450\ub294 \ubc29\uc2dd\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>\uc57d\ud55c \uc815\ubcf4 \uc0ac\uc804 \ubd84\ud3ec (Weakly Informative Prior):<\/strong> &#8220;\uc815\ud655\ud788\ub294 \ubaa8\ub974\uc9c0\ub9cc, \ud130\ubb34\ub2c8\uc5c6\ub294 \uac12\uc740 \uc544\ub2d0 \uac83\uc774\ub2e4.&#8221;\n<ul class=\"wp-block-list\">\n<li>\uc644\uc804\ud55c \ubb34\uc815\ubcf4\ubcf4\ub2e4\ub294 \ub0ab\uace0, \ud2b9\uc815 \uc774\ub860\uc5d0 \ub108\ubb34 \uce58\uc6b0\uce58\uc9c0 \uc54a\ub3c4\ub85d \ud569\ub2c8\ub2e4. \ud45c\ubcf8 \ud06c\uae30\uac00 \uc791\uc744 \ub54c \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>\uc815\ubcf4\uc801 \uc0ac\uc804 \ubd84\ud3ec (Informative Prior):<\/strong> &#8220;\uae30\uc874 \uc5f0\uad6c\uc5d0 \ub530\ub974\uba74 \ud3c9\uade0 130 \uc815\ub3c4\uc77c \uac83\uc774\ub2e4.&#8221;\n<ul class=\"wp-block-list\">\n<li>\uc815\uaddc\ubd84\ud3ec <math data-latex=\"N(130, 5)\"><semantics><mrow><mi>N<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mn>130<\/mn><mo separator=\"true\">,<\/mo><mn>5<\/mn><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">N(130, 5)<\/annotation><\/semantics><\/math> \ucc98\ub7fc \uad6c\uccb4\uc801\uc778 \ud3c9\uade0\uacfc \ubd84\uc0b0\uc744 \uc9c0\uc815\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">3. MCMC \uc0d8\ud50c\ub9c1\uacfc HMC<\/h2>\n\n\n\n<p>\ubca0\uc774\uc9c0\uc548 \ucd94\uc815\uc740 \ubcf5\uc7a1\ud55c \uc801\ubd84 \uacc4\uc0b0\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 <strong>MCMC(Markov Chain Monte Carlo)<\/strong> \uc2dc\ubbac\ub808\uc774\uc158\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.1 \uae30\uc874 \ubc29\ubc95: MH\uc640 Gibbs<\/h3>\n\n\n\n<p>\uacfc\uac70\uc5d0\ub294 Metropolis-Hastings (MH)\ub098 Gibbs \uc0d8\ud50c\ub7ec\ub97c \uc37c\uc2b5\ub2c8\ub2e4. \ud558\uc9c0\ub9cc \ubaa8\ud615\uc774 \ubcf5\uc7a1\ud574\uc9c0\uba74(\ucc28\uc6d0\uc774 \ub192\uc544\uc9c0\uba74) \uc774 \uc54c\uace0\ub9ac\uc998\ub4e4\uc740 &#8220;\ub79c\ub364 \uc6cc\ud06c(Random Walk)&#8221; \ubc29\uc2dd\uc774\ub77c \ud6a8\uc728\uc774 \ub5a8\uc5b4\uc9c0\uace0 \uc2dc\uac04\uc774 \uc624\ub798 \uac78\ub9bd\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.2 \ud604\ub300\uc801 \ubc29\ubc95: Hamiltonian Monte Carlo (HMC)\uc640 NUTS<\/h3>\n\n\n\n<p>\uc774 \ucc55\ud130\uc5d0\uc11c \uac15\uc870\ud558\ub294 \uac83\uc740 <strong>HMC<\/strong>\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\ube44\uc720:<\/strong> MH\uac00 \ub208 \uac00\ub9ac\uace0 \uc0b0\uc744 \ub354\ub4ec\uc5b4 \ub0b4\ub824\uac00\ub294 \ub4f1\uc0b0\uac1d\uc774\ub77c\uba74, HMC\ub294 \ubb3c\ub9ac\ud559\uc758 \uc6d0\ub9ac\ub97c \uc774\uc6a9\ud574 \uc370\ub9e4\ub97c \ud0c0\uace0 \ub4f1\uace0\uc120(\uc804\ud615\uc801 \uc9d1\ud569, Typical Set)\uc744 \ubbf8\ub044\ub7ec\uc9c0\ub4ef \uc774\ub3d9\ud558\ub294 \uac83\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>NUTS (No-U-Turn Sampler):<\/strong> HMC\ub294 \uc124\uc815\ud574\uc57c \ud560 \ud30c\ub77c\ubbf8\ud130\uac00 \ub9ce\uc740\ub370, NUTS\ub294 \uc774\ub97c \uc790\ub3d9\uc73c\ub85c \uc870\uc815\ud558\uc5ec \uc0ac\uc6a9\uc790\uac00 \uc4f0\uae30 \uc27d\uac8c \ub9cc\ub4e0 \uc54c\uace0\ub9ac\uc998\uc785\ub2c8\ub2e4. <code>Stan<\/code>\uacfc <code>blavaan<\/code>\uc774 \uc774 \ubc29\uc2dd\uc744 \uc501\ub2c8\ub2e4.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">4. \uc2e4\uc2b5: BSEM \ubd84\uc11d \uc2dc\ub098\ub9ac\uc624 \ubc0f \ub370\uc774\ud130 \uc0dd\uc131<\/h2>\n\n\n\n<p>\uc774\uc81c \uc2e4\uc81c \uad50\uc721 \ub370\uc774\ud130\ub97c \uac00\uc815\ud558\uc5ec \ubd84\uc11d\ud574 \ubd05\uc2dc\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4.1 \uc2dc\ub098\ub9ac\uc624: \uad50\uc0ac\uc758 \uc790\uc728\uc131 \uc9c0\uc9c0\uac00 \ud559\uc0dd\uc758 \ud559\uc5c5 \uc131\ucde8\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\uc5f0\uad6c \ubb38\uc81c:<\/strong> \uacfc\ud559 \uad50\uc0ac\uc758 \uc790\uc728\uc131 \uc9c0\uc9c0(Support)\uac00 \ud559\uc0dd\uc758 \uacfc\ud559 \ud765\ubbf8(Interest)\ub97c \ub9e4\uac1c\ub85c \ud559\uc5c5 \uc131\ucde8(Achievement)\uc5d0 \uc601\ud5a5\uc744 \ubbf8\uce58\ub294\uac00?<\/li>\n\n\n\n<li><strong>\ubd84\uc11d \ub3c4\uad6c:<\/strong> R (jamovi Rj Editor \ud65c\uc6a9 \uac00\ub2a5) \ubc0f <code>blavaan<\/code> \ud328\ud0a4\uc9c0.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">4.2 \ub370\uc774\ud130 \uc0dd\uc131 (R Code)<\/h3>\n\n\n\n<p>\uba3c\uc800 \ubaa8\uc758 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<p>R<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \ud544\uc694\ud55c \ud328\ud0a4\uc9c0 \ub85c\ub4dc (jamovi Rj Editor\uc5d0\uc11c \uc2e4\ud589 \uc2dc install.packages\ub294 \uc0dd\ub7b5 \uac00\ub2a5\ud560 \uc218 \uc788\uc74c)\nif (!require(\"lavaan\")) install.packages(\"lavaan\")\nif (!require(\"blavaan\")) install.packages(\"blavaan\")\nif (!require(\"semTools\")) install.packages(\"semTools\")\n\nset.seed(2026)\n\n# \ud45c\ubcf8 \ud06c\uae30\nn &lt;- 300\n\n# \uc7a0\uc7ac\ubcc0\uc218 \uc0dd\uc131\n# Support (\uad50\uc0ac \uc9c0\uc9c0), Interest (\ud765\ubbf8), Achieve (\uc131\ucde8)\n# \uad6c\uc870: Support -&gt; Interest -&gt; Achieve\nSupport &lt;- rnorm(n, 0, 1)\nInterest &lt;- 0.6 * Support + rnorm(n, 0, 0.8) # \ub9e4\uac1c\ubcc0\uc218 (\uacbd\ub85c\uacc4\uc218 0.6)\nAchieve &lt;- 0.5 * Interest + 0.3 * Support + rnorm(n, 0, 0.8) # \uc885\uc18d\ubcc0\uc218\n\n# \uad00\uce21\ubcc0\uc218 \uc0dd\uc131 (\uce21\uc815\ubaa8\ud615)\n# \uac01 \uc7a0\uc7ac\ubcc0\uc218\ub2f9 3\uac1c\uc758 \ubb38\ud56d\ny_data &lt;- data.frame(\n  S1 = 1.0*Support + rnorm(n, 0, 0.5),\n  S2 = 0.9*Support + rnorm(n, 0, 0.5),\n  S3 = 1.1*Support + rnorm(n, 0, 0.5),\n  \n  I1 = 1.0*Interest + rnorm(n, 0, 0.5),\n  I2 = 0.8*Interest + rnorm(n, 0, 0.5),\n  I3 = 1.2*Interest + rnorm(n, 0, 0.5),\n  \n  A1 = 1.0*Achieve + rnorm(n, 0, 0.5),\n  A2 = 0.9*Achieve + rnorm(n, 0, 0.5),\n  A3 = 1.0*Achieve + rnorm(n, 0, 0.5)\n)\n\nhead(y_data)\n<\/code><\/pre>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-c14b273d-1309-4e1e-b139-bab7d2d45d9d\" href=\"http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/chap38.csv\">chap38<\/a><a href=\"http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/chap38.csv\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-c14b273d-1309-4e1e-b139-bab7d2d45d9d\">\ub2e4\uc6b4\ub85c\ub4dc<\/a><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">4.3 BSEM \ubaa8\ud615 \uba85\uc138 \ubc0f \ucd94\uc815 (<code>blavaan<\/code>)<\/h3>\n\n\n\n<p><code>blavaan<\/code>\uc740 R\uc758 <code>lavaan<\/code> \ubb38\ubc95\uc744 \uadf8\ub300\ub85c \uc4f0\uba74\uc11c \ubca0\uc774\uc9c0\uc548 \ucd94\uc815\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<p>R<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \ubaa8\ud615 \uba85\uc138 (lavaan \ubb38\ubc95)\nmodel_syntax &lt;- '\n  # \uce21\uc815 \ubaa8\ud615\n  Support =~ S1 + S2 + S3\n  Interest =~ I1 + I2 + I3\n  Achieve =~ A1 + A2 + A3\n  \n  # \uad6c\uc870 \ubaa8\ud615\n  Interest ~ a*Support\n  Achieve ~ b*Interest + c*Support\n  \n  # \uac04\uc811 \ud6a8\uacfc\n  ab := a*b\n'\n\n# \ubca0\uc774\uc9c0\uc548 \ucd94\uc815 (Default priors \uc0ac\uc6a9)\n# mcmcfile=TRUE\ub85c \uc124\uc815\ud558\uba74 Stan \ucf54\ub4dc \ud655\uc778 \uac00\ub2a5\nfit_bayes &lt;- bsem(model_syntax, data = y_data, \n                  n.chains = 3, burnin = 500, sample = 1000,\n                  target = \"stan\") \n\nsummary(fit_bayes)\n<\/code><\/pre>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong>WaurimaL\uc758 \ud301:<\/strong> jamovi\uc758 <code>semlj<\/code> \ubaa8\ub4c8\uc744 \uc0ac\uc6a9\ud558\uba74 \uba54\ub274 \ubc29\uc2dd\uc73c\ub85c SEM\uc744 \ub3cc\ub9b4 \uc218 \uc788\uc9c0\ub9cc, \ubcf8\ubb38\uc5d0\uc11c \ub2e4\ub8e8\ub294 \uc138\ubc00\ud55c \ubca0\uc774\uc9c0\uc548 \uc124\uc815(HMC, NUTS)\uc744 \uc704\ud574\uc11c\ub294 \uc704\uc640 \uac19\uc774 R \ucf54\ub4dc\ub97c <code>Rj Editor<\/code>\uc5d0 \ubd99\uc5ec\ub123\uc5b4 \uc2e4\ud589\ud558\ub294 \uac83\uc774 \uac00\uc7a5 \uc815\ud655\ud569\ub2c8\ub2e4.<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\">5. \uc218\ub834 \uc9c4\ub2e8 (Convergence Diagnostics)<\/h2>\n\n\n\n<p>\ubca0\uc774\uc9c0\uc548 \ubd84\uc11d\uc5d0\uc11c\ub294 \uacb0\uacfc\uac00 \ud558\ub098\uc758 \uc810(point)\uc73c\ub85c \uc218\ub834\ud558\ub294 \uac83\uc774 \uc544\ub2c8\ub77c, \ubd84\ud3ec\ub85c \uc218\ub834\ud574\uc57c \ud569\ub2c8\ub2e4. \ubd84\uc11d\uc774 \uc798 \ub418\uc5c8\ub294\uc9c0 \ud655\uc778\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>Trace Plots (\uc774\ub825 \ub3c4\ud45c):<\/strong> \uc560\ubc8c\ub808(caterpillar)\ucc98\ub7fc \ub6b1\ub6b1\ud558\uace0 \ud138\uc774 \ub09c \ubaa8\uc591\uc774\uc5b4\uc57c \ud569\ub2c8\ub2e4. \uc0ac\uc2ac(chain)\ub4e4\uc774 \uc11c\ub85c \uc798 \uc11e\uc5ec \uc788\uc5b4\uc57c \ud569\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>Posterior Density Plots (\uc0ac\ud6c4 \ubc00\ub3c4 \ub3c4\ud45c):<\/strong> \ub9e4\ub044\ub7ec\uc6b4 \uc815\uaddc\ubd84\ud3ec \ubaa8\uc591\uc774\uba74 \uc88b\uc2b5\ub2c8\ub2e4. \ubd09\uc6b0\ub9ac\uac00 \ub450 \uac1c(bimodality)\ub77c\uba74 \uc218\ub834\uc5d0 \ubb38\uc81c\uac00 \uc788\ub294 \uac83\uc785\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>Autocorrelation (\uc790\uae30\uc0c1\uad00):<\/strong> \uc2dc\ucc28(lag)\uac00 \ub298\uc5b4\ub0a0\uc218\ub85d \uc0c1\uad00\uc774 \ube68\ub9ac 0\uc73c\ub85c \ub5a8\uc5b4\uc838\uc57c \ud569\ub2c8\ub2e4.<\/li>\n\n\n\n<li><math data-latex=\"\\hat{R}\"><semantics><mover><mi>R<\/mi><mo stretchy=\"false\" class=\"tml-capshift\" style=\"math-style:normal;math-depth:0;\">^<\/mo><\/mover><annotation encoding=\"application\/x-tex\">\\hat{R}<\/annotation><\/semantics><\/math><strong> (Potential Scale Reduction Factor):<\/strong> \uc0ac\uc2ac \uac04 \ubd84\uc0b0\uacfc \uc0ac\uc2ac \ub0b4 \ubd84\uc0b0\uc758 \ube44\uc728\uc785\ub2c8\ub2e4. 1.0\uc5d0 \uac00\uae4c\uc6cc\uc57c \ud558\uba70, <strong>1.01\ubcf4\ub2e4 \ud06c\uba74<\/strong> \uc218\ub834\ud558\uc9c0 \uc54a\uc740 \uac83\uc73c\ub85c \ubd05\ub2c8\ub2e4. \ucd5c\uadfc Stan\uc5d0\uc11c\ub294 <strong>Split <\/strong><math data-latex=\"\\hat{R}\"><semantics><mover><mi>R<\/mi><mo stretchy=\"false\" class=\"tml-capshift\" style=\"math-style:normal;math-depth:0;\">^<\/mo><\/mover><annotation encoding=\"application\/x-tex\">\\hat{R}<\/annotation><\/semantics><\/math>\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub354 \ubbfc\uac10\ud558\uac8c \uc9c4\ub2e8\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n\n\n\n<p>R<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \uc218\ub834 \uc9c4\ub2e8 \uadf8\ub798\ud504 (blavaan \uae30\ub2a5)\nplot(fit_bayes, type = \"trace\")\nplot(fit_bayes, type = \"acf\")\nblavInspect(fit_bayes, \"neff\") # \uc720\ud6a8 \ud45c\ubcf8 \ud06c\uae30 \ud655\uc778\nblavInspect(fit_bayes, \"psrf\") # R-hat \ud655\uc778\n<\/code><\/pre>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"799\" src=\"http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1-1024x799.png\" alt=\"\" class=\"wp-image-688\" srcset=\"http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1-1024x799.png 1024w, http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1-300x234.png 300w, http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1-768x599.png 768w, http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1-624x487.png 624w, http:\/\/waurimal.kr\/wp-content\/uploads\/2026\/01\/fig38-1.png 1106w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">6. \ubaa8\ud615 \ud3c9\uac00 \ubc0f \uc120\ud0dd<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">6.1 \uc0ac\ud6c4 \uc608\uce21 \uc810\uac80 (Posterior Predictive Checking, PPC)<\/h3>\n\n\n\n<p>\ub0b4 \ubaa8\ud615\uc774 \uc0dd\uc131\ud55c \uac00\uc0c1\uc758 \ub370\uc774\ud130(<math data-latex=\"\\tilde{y}\"><semantics><mover><mi>y<\/mi><mo stretchy=\"false\" style=\"math-style:normal;math-depth:0;\">~<\/mo><\/mover><annotation encoding=\"application\/x-tex\">\\tilde{y}<\/annotation><\/semantics><\/math>)\uac00 \uc2e4\uc81c \ub370\uc774\ud130(<math data-latex=\"y\"><semantics><mi>y<\/mi><annotation encoding=\"application\/x-tex\">y<\/annotation><\/semantics><\/math>)\uc640 \uc5bc\ub9c8\ub098 \ube44\uc2b7\ud55c\uc9c0 \ubd05\ub2c8\ub2e4.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Bayesian p-value:<\/strong> \uac00\uc0c1 \ub370\uc774\ud130\uac00 \uc2e4\uc81c \ub370\uc774\ud130\ubcf4\ub2e4 \uadf9\ub2e8\uc801\uc778 \ube44\uc728\uc785\ub2c8\ub2e4. 0.5 \uadfc\ucc98\uba74 \ubaa8\ud615\uc774 \ub370\uc774\ud130\ub97c \uc798 \uc124\uba85\ud558\ub294 \uac83\uc774\uace0, 0.05 \ubbf8\ub9cc\uc774\ub098 0.95 \ucd08\uacfc\uba74 \uc801\ud569\ub3c4\uc5d0 \ubb38\uc81c\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">6.2 \ubaa8\ud615 \ube44\uad50 \uc9c0\uc218<\/h3>\n\n\n\n<p>\uc5b4\ub5a4 \ubaa8\ud615\uc774 \uc88b\uc740 \ubaa8\ud615\uc77c\uae4c\uc694?<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>BIC:<\/strong> \uc804\ud1b5\uc801\uc778 \uc9c0\uc218\uc774\uc9c0\ub9cc \ubca0\uc774\uc9c0\uc548\uc5d0\uc11c\ub294 \ud55c\uacc4\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>DIC:<\/strong> \ubca0\uc774\uc9c0\uc548 \ud3b8\ucc28 \uc815\ubcf4 \uae30\uc900. \uc791\uc744\uc218\ub85d \uc88b\uc2b5\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>LOOIC (Leave-One-Out Information Criterion):<\/strong> \ucd5c\uadfc \uac00\uc7a5 \uad8c\uc7a5\ub418\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \ud558\ub098\ub97c \ube7c\uace0 \uc608\uce21\ud574 \ubcf4\ub294 \uad50\ucc28\ud0c0\ub2f9\ub3c4(LOOCV) \uac1c\ub150\uc744 \uadfc\uc0ac\ud55c \uac83\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n\n\n\n<p>R<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \uc801\ud569\ub3c4 \uc9c0\uc218 \ud655\uc778\nfitMeasures(fit_bayes, c(\"bic\", \"dic\", \"looic\"))\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">6.3 \ubca0\uc774\uc9c0\uc548 \ubaa8\ud615 \ud3c9\uade0\ud654 (Bayesian Model Averaging, BMA)<\/h3>\n\n\n\n<p>\ud558\ub098\uc758 \ubaa8\ud615\ub9cc \uc120\ud0dd\ud558\ub294 \uac83\uc740 \uc704\ud5d8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. BMA\ub294 \uc5ec\ub7ec \uac00\ub2a5\ud55c \ubaa8\ud615\ub4e4\uc758 \uacb0\uacfc\ub97c \uadf8 \ubaa8\ud615\uc774 \ub9de\uc744 \ud655\ub960(Posterior Model Probability)\ub85c \uac00\uc911 \ud3c9\uade0\ud558\uc5ec \uc608\uce21\ub825\uc744 \ub192\uc785\ub2c8\ub2e4. \uad50\uc721 \ud604\uc7a5\ucc98\ub7fc \ubd88\ud655\uc2e4\uc131\uc774 \ud070 \uacbd\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">7. \uace0\uae09 \ud655\uc7a5: \uc0ac\uc804 \ubd84\ud3ec\ub97c \ud1b5\ud55c \uc720\uc5f0\uc131<\/h2>\n\n\n\n<p>BSEM\uc758 \uc9c4\uc815\ud55c \ud798\uc740 &#8216;\uc720\uc5f0\uc131&#8217;\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">7.1 \uadfc\uc0ac 0 \uc0ac\uc804 \ubd84\ud3ec (Near-Zero Priors)\uc640 CFA<\/h3>\n\n\n\n<p>\uc804\ud1b5\uc801 CFA\uc5d0\uc11c\ub294 \uad50\ucc28 \uc801\uc7ac\ub7c9(cross-loading)\uc744 \ubb34\uc870\uac74 0\uc73c\ub85c \uace0\uc815\ud569\ub2c8\ub2e4. \uc774\ub294 \ud604\uc2e4\uc801\uc774\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4. BSEM\uc5d0\uc11c\ub294 \uc774\ub97c &#8220;\uc815\ud655\ud788 0\uc740 \uc544\ub2c8\uc9c0\ub9cc 0\uc5d0 \uc544\uc8fc \uac00\uae4c\uc6b4(Approximately Zero)&#8221; \uc815\uaddc\ubd84\ud3ec <math data-latex=\"N(0, 0.01)\"><semantics><mrow><mi>N<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mn>0<\/mn><mo separator=\"true\">,<\/mo><mn>0.01<\/mn><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">N(0, 0.01)<\/annotation><\/semantics><\/math>\ub85c \uc124\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\uc774\ub807\uac8c \ud558\uba74 \ubaa8\ud615 \uc801\ud569\ub3c4\ub97c \uac1c\uc120\ud558\uba74\uc11c\ub3c4 \uc774\ub860\uc801 \uad6c\uc870\ub97c \uc720\uc9c0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">7.2 \uadfc\uc0ac \uce21\uc815 \ubd88\ubcc0\uc131 (Approximate Measurement Invariance)<\/h3>\n\n\n\n<p>\ub0a8\ub140 \uc9d1\ub2e8 \uac04 \ube44\uad50\ub97c \ud560 \ub54c, \uc808\ud3b8\uc774\ub098 \uc801\uc7ac\ub7c9\uc774 &#8216;\uc644\ubcbd\ud788&#8217; \uac19\uc744 \ud544\uc694\ub294 \uc5c6\uc2b5\ub2c8\ub2e4. \uadf8 \ucc28\uc774\uac00 <strong>\uadfc\uc0ac\uc801\uc73c\ub85c 0 (<math data-latex=\"Difference \\sim N(0, 0.001)\"><semantics><mrow><mi>D<\/mi><mi>i<\/mi><mi>f<\/mi><mi>f<\/mi><mi>e<\/mi><mi>r<\/mi><mi>e<\/mi><mi>n<\/mi><mi>c<\/mi><mi>e<\/mi><mo>\u223c<\/mo><mi>N<\/mi><mo form=\"prefix\" stretchy=\"false\">(<\/mo><mn>0<\/mn><mo separator=\"true\">,<\/mo><mn>0.001<\/mn><mo form=\"postfix\" stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">Difference \\sim N(0, 0.001)<\/annotation><\/semantics><\/math>)<\/strong>\uc774\ub77c\uace0 \uac00\uc815\ud568\uc73c\ub85c\uc368, \uc5c4\uaca9\ud55c \ubd88\ubcc0\uc131 \uae30\uac01 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">7.3 \ubca0\uc774\uc9c0\uc548 \uc815\uaddc\ud654 (Regularization): Ridge &amp; Lasso<\/h3>\n\n\n\n<p>\ud45c\ubcf8\uc740 \uc801\uc740\ub370 \ubcc0\uc218\uac00 \ub9ce\uc744 \ub54c(\uacfc\uc801\ud569 \uc704\ud5d8), \uacc4\uc218\ub97c 0\uc73c\ub85c \uc218\ucd95(shrinkage)\uc2dc\ud0a4\ub294 \uc0ac\uc804 \ubd84\ud3ec\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Ridge:<\/strong> \uc815\uaddc\ubd84\ud3ec \uc0ac\uc804 \ubd84\ud3ec \uc0ac\uc6a9 (L2-norm).<\/li>\n\n\n\n<li><strong>Lasso:<\/strong> \uc774\uc911 \uc9c0\uc218(Double Exponential) \ub610\ub294 \ub77c\ud50c\ub77c\uc2a4 \ubd84\ud3ec \uc0ac\uc6a9 (L1-norm). \uacc4\uc218\ub97c 0\uc73c\ub85c \ub354 \uac15\ud558\uac8c \ubcf4\ub0c5\ub2c8\ub2e4.<\/li>\n<\/ul>\n\n\n\n<p>R<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \uc608: Lasso \ud328\ub110\ud2f0\ub97c \uc801\uc6a9\ud55c \ubaa8\ud615 (blavaan syntax \uc608\uc2dc)\n# dp\ub294 double exponential(Lasso)\uc758 \ud30c\ub77c\ubbf8\ud130\n# prior(\"double_exp(0, 1)\", coefficients) \uc640 \uac19\uc740 \ud615\ud0dc\ub85c \uc124\uc815 \uac00\ub2a5\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">8. \uacb0\ub860<\/h2>\n\n\n\n<p>\ubca0\uc774\uc9c0\uc548 SEM\uc740 \ub2e8\uc21c\ud55c &#8216;\ub610 \ub2e4\ub978 \ucd94\uc815 \ubc29\ubc95&#8217;\uc774 \uc544\ub2d9\ub2c8\ub2e4. \uc774\uac83\uc740 \uc5f0\uad6c\uc790\uac00 \uac00\uc9c4 <strong>\uc0ac\uc804 \uc9c0\uc2dd<\/strong>\uc744 \ubaa8\ud615\uc5d0 \uba85\uc2dc\uc801\uc73c\ub85c \ud3ec\ud568\ud558\uace0, <strong>\ubd88\ud655\uc2e4\uc131<\/strong>\uc744 \uc815\uc9c1\ud558\uac8c \ub2e4\ub8e8\uba70, \uc5c4\uaca9\ud55c \ube48\ub3c4\uc8fc\uc758 \uc81c\uc57d\uc744 <strong>\uc720\uc5f0\ud558\uac8c<\/strong> \ud480\uc5b4\uc8fc\ub294 \uc2e4\uc6a9\uc801\uc778 \ub3c4\uad6c\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\uc774 \uae00\uc5d0\uc11c \ubc30\uc6b4 HMC \uc54c\uace0\ub9ac\uc998, \uc218\ub834 \uc9c4\ub2e8, LOOIC, \uadf8\ub9ac\uace0 \uc815\ubcf4\uc801 \uc0ac\uc804 \ubd84\ud3ec\uc758 \ud65c\uc6a9\uc740 \uc5ec\ub7ec\ubd84\uc774 \uad50\uc721 \ud604\uc7a5\uc758 \ubcf5\uc7a1\ud55c \ub370\uc774\ud130\ub97c \ub354 \uae4a\uc774 \uc774\ud574\ud558\ub294 \ub370 \ud070 \ub3c4\uc6c0\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\ucc38\uace0\ubb38\ud5cc<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Betancourt, M. (2018). <em>A conceptual introduction to Hamiltonian Monte Carlo<\/em>. arXiv preprint arXiv:1701.02434.<\/li>\n\n\n\n<li>Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., &amp; Rubin, D. B. (2014). <em>Bayesian data analysis<\/em> (3rd ed.). Chapman and Hall\/CRC.<\/li>\n\n\n\n<li>Kaplan, D., &amp; Depaoli, S. (2012). Bayesian structural equation modeling. In R. H. Hoyle (Ed.), <em>Handbook of structural equation modeling<\/em> (pp. 650-673). Guilford Press.<\/li>\n\n\n\n<li>Muth\u00e9n, B. O., &amp; Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. <em>Psychological Methods, 17<\/em>(3), 313\u2013335.<\/li>\n\n\n\n<li>Vehtari, A., Gelman, A., &amp; Gabry, J. (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. <em>Statistics and Computing, 27<\/em>(5), 1413\u20131432.<\/li>\n\n\n\n<li>van de Schoot, R., Winter, S. D., Zondervan-Zwijnenburg, M., Ryan, O., &amp; Depaoli, S. (2017). A systematic review of Bayesian applications in psychology: The last 25 years. <em>Psychological Methods, 22<\/em>(2), 217\u2013239.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc548\ub155\ud558\uc138\uc694. \uc774\ubc88\uc5d0\ub294 \ud1b5\uacc4\ud559\uc758 \uc0c8\ub85c\uc6b4 \uc9c0\ud3c9\uc778 \ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM)\uc758 \uc138\uacc4\ub85c \ub4e4\uc5b4\uac00\ub294 \uac83\uc744 \ub3d5\uace0\uc790 \ud569\ub2c8\ub2e4. 2012\ub144 \ucd08\ud310 \uc774\ud6c4, \ubca0\uc774\uc9c0\uc548 \ucd94\ub860\uc740 \uc0ac\ud68c\uacfc\ud559 \ubc0f \ud589\ub3d9\uacfc\ud559 \ubd84\uc57c\uc5d0\uc11c \ube48\ub3c4\uc8fc\uc758(Frequentist) \ubc29\ubc95\ub860\uc758 \uac15\ub825\ud55c \ub300\uc548\uc73c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uc774\ubc88 \ub0b4\uc6a9\uc5d0\uc11c\ub294 Hamiltonian Monte Carlo (HMC) \uc54c\uace0\ub9ac\uc998\uacfc Stan \uac19\uc740 \uc624\ud508 \uc18c\uc2a4 \uc18c\ud504\ud2b8\uc6e8\uc5b4\uc758 \ubc1c\uc804\uc5d0 \ud798\uc785\uc5b4 \ub354\uc6b1 \uc815\uad50\ud574\uc9c4 BSEM\uc758 \uae30\ucd08\uc640 \ud655\uc7a5\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. <a class=\"read-more\" href=\"http:\/\/waurimal.kr\/?p=687\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_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":[300],"tags":[392,199,166,393,301,391],"class_list":["post-687","post","type-post","status-publish","format-standard","hentry","category-sem","tag-hmc","tag-r","tag-sem","tag-stan","tag-301","tag-391"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Chap 38. \ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM) - WaurimaL<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/waurimal.kr\/?p=687\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Chap 38. \ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM) - WaurimaL\" \/>\n<meta property=\"og:description\" content=\"\uc548\ub155\ud558\uc138\uc694. \uc774\ubc88\uc5d0\ub294 \ud1b5\uacc4\ud559\uc758 \uc0c8\ub85c\uc6b4 \uc9c0\ud3c9\uc778 \ubca0\uc774\uc9c0\uc548 \uad6c\uc870\ubc29\uc815\uc2dd \ubaa8\ud615(Bayesian Structural Equation Modeling, BSEM)\uc758 \uc138\uacc4\ub85c \ub4e4\uc5b4\uac00\ub294 \uac83\uc744 \ub3d5\uace0\uc790 \ud569\ub2c8\ub2e4. 2012\ub144 \ucd08\ud310 \uc774\ud6c4, \ubca0\uc774\uc9c0\uc548 \ucd94\ub860\uc740 \uc0ac\ud68c\uacfc\ud559 \ubc0f \ud589\ub3d9\uacfc\ud559 \ubd84\uc57c\uc5d0\uc11c \ube48\ub3c4\uc8fc\uc758(Frequentist) \ubc29\ubc95\ub860\uc758 \uac15\ub825\ud55c \ub300\uc548\uc73c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uc774\ubc88 \ub0b4\uc6a9\uc5d0\uc11c\ub294 Hamiltonian Monte Carlo (HMC) \uc54c\uace0\ub9ac\uc998\uacfc Stan \uac19\uc740 \uc624\ud508 \uc18c\uc2a4 \uc18c\ud504\ud2b8\uc6e8\uc5b4\uc758 \ubc1c\uc804\uc5d0 \ud798\uc785\uc5b4 \ub354\uc6b1 \uc815\uad50\ud574\uc9c4 BSEM\uc758 \uae30\ucd08\uc640 \ud655\uc7a5\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. 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