{"id":257,"date":"2019-07-14T22:02:07","date_gmt":"2019-07-14T13:02:07","guid":{"rendered":"https:\/\/ujicya.jp\/wordpress\/?p=257"},"modified":"2019-09-01T17:59:44","modified_gmt":"2019-09-01T08:59:44","slug":"latentclassmodel-1","status":"publish","type":"post","link":"https:\/\/ujicya.jp\/blog-mapping\/latentclassmodel-1\/","title":{"rendered":"R\u3067\u6f5c\u5728\u30af\u30e9\u30b9\u30e2\u30c7\u30eb poLCA (1)"},"content":{"rendered":"\n<p>\u6f5c\u5728\u30af\u30e9\u30b9\u30e2\u30c7\u30eb\uff08Latent class model\uff09\u306f\uff0c\u7d71\u8a08\u30e2\u30c7\u30eb\u306e\u4e00\u7a2e\u3067\u3042\u308a\uff0c\u30a2\u30f3\u30b1\u30fc\u30c8\u8abf\u67fb\u306e\u5206\u6790\u306a\u3069\u306b\u4f7f\u308f\u308c\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u672c\u30e2\u30c7\u30eb\u3067\u306f\uff0c\u56de\u7b54\u8005\u304c\u7570\u306a\u308b\u50be\u5411\u3092\u6301\u3064\u8907\u6570\u306e\u96c6\u56e3\uff08\u30af\u30e9\u30b9\uff09\u306b\u3088\u3063\u3066\u69cb\u6210\u3055\u308c\u308b\u3068\u60f3\u5b9a\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u3064\u307e\u308a\uff0c\u56de\u7b54\u8005\u306f\uff0c\u5358\u4e00\u306e\u6bcd\u96c6\u56e3\u306e\u30b5\u30f3\u30d7\u30eb\u3067\u306f\u306a\u304f\uff0c\u8907\u6570\u306e\u90e8\u5206\u6bcd\u96c6\u56e3\u304b\u3089\u306e\u30b5\u30f3\u30d7\u30eb\u3067\u3042\u308b\u3068\u8003\u3048\u308b\u306e\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u305d\u3057\u3066\uff0c\u985e\u4f3c\u3057\u305f\u56de\u7b54\u30d1\u30bf\u30fc\u30f3\u3092\u6301\u3064\u4eba\u3092\u30af\u30e9\u30b9\u306b\u7e2e\u7d04\u3059\u308b\u3053\u3068\u3067\uff0c\u56de\u7b54\u8005\u306e\u30bb\u30b0\u30e1\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u3092\u304a\u3053\u306a\u3046\u306e\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u3053\u308c\u3092\uff0c\u6f5c\u5728\u30af\u30e9\u30b9\u5206\u6790\uff08Latent class analysis\uff09\u3068\u3044\u3044\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u3055\u3089\u306b\uff0c\u5f97\u3089\u308c\u305f\u30af\u30e9\u30b9\u3068\uff0c\u56de\u7b54\u8005\u306e\u500b\u4eba\u5c5e\u6027\uff08\u5e74\u9f62\uff0c\u6027\u5225\u306a\u3069\uff09\u3092\u7528\u3044\u3066\u56de\u5e30\u5206\u6790\u3092\u304a\u3053\u306a\u3046\u3053\u3068\u3067\uff0c\u300c\u3069\u306e\u3088\u3046\u306a\u7279\u5fb4\u3092\u6301\u3063\u305f\u4eba\u304c\uff0c\u3069\u306e\u30af\u30e9\u30b9\u306b\u5c5e\u3057\uff0c\u3069\u306e\u3088\u3046\u306a\u56de\u7b54\u3092\u3057\u3084\u3059\u3044\u306e\u304b\u300d\u3092\u5206\u6790\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\uff0e<br>\uff08\u30af\u30e9\u30b9\u306e\u5171\u5909\u91cf\u3068\u3057\u3066\uff0c\u500b\u4eba\u5c5e\u6027\u3092\u5c0e\u5165\u3059\u308b\u3053\u3068\uff09<\/p>\n\n\n\n<p>\u3053\u306e\u5834\u5408\uff0c\u5358\u306a\u308b\u6f5c\u5728\u30af\u30e9\u30b9\u30e2\u30c7\u30eb\u3067\u306f\u306a\u304f\uff0c\u6f5c\u5728\u30af\u30e9\u30b9\u56de\u5e30\u30e2\u30c7\u30eb\uff08Latent class regression model\uff09\u3092\u7528\u3044\u308b\u3053\u3068\u306b\u306a\u308a\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u305d\u308c\u3067\u306f\uff0cR\u3092\u4f7f\u3063\u3066\u6f5c\u5728\u30af\u30e9\u30b9\u5206\u6790\u3092\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u4eca\u56de\u306f\uff0c\u6700\u521d\u306e\u5206\u6790\u306b\u4f7f\u3046\u30c7\u30fc\u30bf\u306e\u4e2d\u8eab\u3092\u898b\u3066\u3044\u304d\u307e\u3059\uff0e<\/p>\n\n\n\n<h2>\u74b0\u5883\u30fb\u6761\u4ef6<\/h2>\n\n\n\n<table class=\"wp-block-table\"><tbody><tr><td>OS<\/td><td>Windows 10 Home<\/td><\/tr><tr><td>\u5b9f\u88c5\u30e1\u30e2\u30ea<\/td><td>8 GB<\/td><\/tr><tr><td>CPU<\/td><td>Intel core i5-3470<\/td><\/tr><tr><td>R<\/td><td>3.6.0<\/td><\/tr><tr><td>\u6f5c\u5728\u30af\u30e9\u30b9\u5206\u6790\u30d1\u30c3\u30b1\u30fc\u30b8<\/td><td>poLCA 1.4.1<br>(Polytomous Variable Latent Class Analysis)<\/td><\/tr><\/tbody><\/table>\n\n\n\n<h2>\u4f7f\u7528\u30c7\u30fc\u30bf<\/h2>\n\n\n\n<p>poLCA\u306e\u4e2d\u306b\u6700\u521d\u304b\u3089\u5165\u3063\u3066\u3044\u308b\u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\uff0c\u300celection\u300d\u3092\u4f7f\u3044\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u3053\u308c\u306f\uff0c2000\u5e74\u306e\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u5927\u7d71\u9818\u9078\u6319\u306b\u304a\u3051\u308b\u4e16\u8ad6\u8abf\u67fb\u3078\u306e\u56de\u7b54\u30c7\u30fc\u30bf\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u5f53\u6642\u306e\u5927\u7d71\u9818\u9078\u306f\uff0c\u300c\u30d6\u30c3\u30b7\u30e5 vs \u30b4\u30a2\u300d\u306e\u4e00\u9a0e\u6253\u3061\u3067\uff0c\u6700\u7d42\u7684\u306b\u30d6\u30c3\u30b7\u30e5\u304c\u52dd\u3061\u307e\u3057\u305f\uff0e<\/p>\n\n\n\n<p>\u3061\u306a\u307f\u306b\uff0c\u9078\u6319\u7d50\u679c\u3092\u3081\u3050\u308a\u300c\u30d6\u30c3\u30b7\u30e5\u5bfe\u30b4\u30a2\u4e8b\u4ef6\u300d\u3068\u3044\u3046\u6cd5\u5ef7\u95d8\u4e89\u306b\u307e\u3067\u767a\u5c55\u3057\u305f\u6fc0\u3057\u3044\u6226\u3044\u3060\u3063\u305f\u3089\u3057\u3044\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u307e\u3042\uff0c\u79c1\u306f\u975e\u5e38\u306b\u5c0f\u3055\u304b\u3063\u305f\u306e\u3067\uff0c\u306a\u306b\u3082\u899a\u3048\u3066\u307e\u305b\u3093\u304c\uff08\u7b11\uff09<\/p>\n\n\n\n<p>\u3055\u3066\uff0c\u30c7\u30fc\u30bf\u306e\u8a73\u7d30\u306b\u5165\u308a\u307e\u3057\u3087\u3046\uff0e<\/p>\n\n\n\n<p>\u3068\u308a\u3042\u3048\u305a\uff0cpoLCA\u3068election\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u3053\u307f\u307e\u3059\uff0e<\/p>\n\n\n\n<pre class=\"wp-block-luxe-blocks-syntaxhighlighter line-numbers language-r\"><code class=\"language-r\">library(poLCA)\ndata(\"election\")<\/code><\/pre>\n\n\n\n<p>\u672c\u30c7\u30fc\u30bf\u306b\u306f\uff0c\u30d6\u30c3\u30b7\u30e5\u3068\u30b4\u30a2\u4e21\u8005\u306b\u5bfe\u3059\u308b\u6295\u7968\u8005\u306e\u8a55\u4fa1\u3068\uff0c\u6295\u7968\u8005\u306e\u500b\u4eba\u5c5e\u6027\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306f\uff0c\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\uff0e<\/p>\n\n\n\n<pre class=\"wp-block-luxe-blocks-syntaxhighlighter line-numbers language-r\"><code class=\"language-r\">str(election)<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code>'data.frame':\t1785 obs. of  17 variables:\n $ MORALG : Factor w\/ 4 levels \"1 Extremely well\",..: 3 4 1 2 2 2 2 2 2 1 \n $ CARESG : Factor w\/ 4 levels \"1 Extremely well\",..: 1 3 2 2 4 3 NA 2 2 1\n $ KNOWG  : Factor w\/ 4 levels \"1 Extremely well\",..: 2 4 2 2 2 3 2 2 2 1 \n $ LEADG  : Factor w\/ 4 levels \"1 Extremely well\",..: 2 3 1 2 3 2 2 2 3 1 \n $ DISHONG: Factor w\/ 4 levels \"1 Extremely well\",..: 3 2 3 2 2 2 4 3 4 4\n $ INTELG : Factor w\/ 4 levels \"1 Extremely well\",..: 2 2 2 2 2 2 2 2 2 1\n $ MORALB : Factor w\/ 4 levels \"1 Extremely well\",..: 1 NA 2 2 1 2 NA 3 2 2\n $ CARESB : Factor w\/ 4 levels \"1 Extremely well\",..: 1 NA 2 3 1 NA 3 4 3 4\n $ KNOWB  : Factor w\/ 4 levels \"1 Extremely well\",..: 2 2 2 2 2 3 2 4 2 2\n $ LEADB  : Factor w\/ 4 levels \"1 Extremely well\",..: 2 3 3 2 2 2 2 4 2 3\n $ DISHONB: Factor w\/ 4 levels \"1 Extremely well\",..: 4 NA 3 3 3 2 4 3 3 3\n $ INTELB : Factor w\/ 4 levels \"1 Extremely well\",..: 2 1 2 1 2 2 NA 4 2 2\n $ VOTE3  : num  2 NA 1 1 2 1 NA 1 1 1 ...\n $ AGE    : num  49 35 57 63 40 77 43 47 26 48 ...\n $ EDUC   : num  5 4 3 4 5 2 4 7 6 3 ...\n $ GENDER : num  1 2 2 1 2 1 1 2 2 2 ...\n $ PARTY  : num  5 3 1 3 7 1 6 1 1 1 ...<\/code><\/pre>\n\n\n\n<p>12\u500b\u306e\u8cea\u7684\u5909\u6570\uff08\u8a55\u4fa1\u5024\uff09\u30685\u500b\u306e\u91cf\u7684\u5909\u6570\uff08\u6295\u7968\u8005\u5c5e\u6027\uff09\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\uff0e<br>\u89b3\u6e2c\u6570\u306f1785\u3067\u3059\uff0e\u305f\u3060\u3057\uff0c\u8a55\u4fa1\u5024\u306b\u95a2\u3059\u308b\u5b8c\u5168\u30c7\u30fc\u30bf\u306f1311\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u5909\u6570\u306e\u5185\u5bb9\u3092\u4ee5\u4e0b\u306b\u307e\u3068\u3081\u307e\u3057\u305f\uff0e<\/p>\n\n\n\n<table class=\"wp-block-table is-style-regular;\"><tbody><tr><td><strong>\u9805\u76ee\u540d<\/strong><\/td><td><strong>\u5bfe\u8c61<\/strong><\/td><td><strong>\u610f\u5473<\/strong><\/td><td><strong>\u5024<\/strong><\/td><\/tr><tr><td>MORALG<\/td><td>\u30b4\u30a2<\/td><td>\u9053\u5fb3\u6027<\/td><td>1  extremely well<br>2  quite well<br>3  not too well<br>4  not well at all<\/td><\/tr><tr><td>CARESG<\/td><td>\u30b4\u30a2 <\/td><td>\u601d\u3044\u3084\u308a\u306e\u6709\u7121<\/td><td>\u3000\u4e0a\u306b\u540c\u3058<\/td><\/tr><tr><td>KNOWG <\/td><td>\u30b4\u30a2 <\/td><td>\u77e5\u8b58\u306e\u8c4a\u5bcc\u3055<\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>LEADG<\/td><td>\u30b4\u30a2 <\/td><td>\u30ea\u30fc\u30c0\u30fc\u30b7\u30c3\u30d7\u306e\u5f37\u3055<\/td><td>\u3000\u4e0a\u306b\u540c\u3058  <\/td><\/tr><tr><td class=\"nowrap\">DISHONG<\/td><td>\u30b4\u30a2 <\/td><td>\u4e0d\u8aa0\u5b9f\u3055<\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>INTELG<\/td><td>\u30b4\u30a2 <\/td><td>\u8ce2\u660e\u3055<\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>MORALB<\/td><td class=\"nowrap\">\u30d6\u30c3\u30b7\u30e5<\/td><td>\u9053\u5fb3\u6027 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>CARESB<\/td><td>\u30d6\u30c3\u30b7\u30e5 <\/td><td>\u601d\u3044\u3084\u308a\u306e\u6709\u7121 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>KNOWB<\/td><td>\u30d6\u30c3\u30b7\u30e5 <\/td><td>\u77e5\u8b58\u306e\u8c4a\u5bcc\u3055 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058  <\/td><\/tr><tr><td>LEADB<\/td><td>\u30d6\u30c3\u30b7\u30e5 <\/td><td>\u30ea\u30fc\u30c0\u30fc\u30b7\u30c3\u30d7\u306e\u5f37\u3055 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td class=\"nowrap\">DISHONB<\/td><td>\u30d6\u30c3\u30b7\u30e5 <\/td><td>\u4e0d\u8aa0\u5b9f\u3055 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>INTELB<\/td><td>\u30d6\u30c3\u30b7\u30e5 <\/td><td>\u8ce2\u660e\u3055 <\/td><td>\u3000\u4e0a\u306b\u540c\u3058 <\/td><\/tr><tr><td>VOTE3<\/td><td>\u6295\u7968\u8005<\/td><td>\u6295\u7968\u7d50\u679c<\/td><td>1  (\u30b4\u30a2)<br>2  (\u30d6\u30c3\u30b7\u30e5)<br>3  (\u305d\u306e\u4ed6)<\/td><\/tr><tr><td>AGE<\/td><td>\u6295\u7968\u8005 <\/td><td>\u5e74\u9f62<\/td><td>18 ~ 97<\/td><\/tr><tr><td>EDUC<\/td><td>\u6295\u7968\u8005 <\/td><td>\u6559\u80b2\u6c34\u6e96<\/td><td>1  (8 grades or less)<br>2  (9-11 grades, no further schooling)<br>3  (High school diploma or equivalency)<br>4  (More than 12 years of schooling, no higher degree)<br>5  (junior or community college level degree)<br>6  (BA level degrees, no advanced degree)<br>7  (Advanced degree)<\/td><\/tr><tr><td>GENDER<\/td><td>\u6295\u7968\u8005 <\/td><td>\u6027\u5225<\/td><td>1  (Male)<br>2  (Female)<\/td><\/tr><tr><td>PARTY<\/td><td>\u6295\u7968\u8005 <\/td><td>\u515a\u6d3e\u306e\u81ea\u5df1\u8a8d\u8b58<\/td><td>1  (Strong Democrat)<br>2  (Weak Democrat)<br>3  (Independent-Democrat)<br>4  (Independent-Independent)<br>5  (Independent-Republican)<br>6  (Weak Republican)<br>7  (Strong Republican)<\/td><\/tr><\/tbody><\/table>\n\n\n\n<p>\u88dc\u8db3\u3068\u3057\u3066\uff0c<strong>\u30b4\u30a2\u306f\u6c11\u4e3b\u515a\uff08Democrat\uff09<\/strong>\u3067\uff0c<strong>\u30d6\u30c3\u30b7\u30e5\u306f\u5171\u548c\u515a\uff08Republican\uff09<\/strong>\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u9053\u5fb3\u6027\u3068\u304b\u601d\u3044\u3084\u308a\u3068\u304b\u4e0d\u8aa0\u5b9f\u3055\u3068\u304b\uff0c\u666e\u901a\u306b\u9023\u95a2\u304c\u3042\u308a\u305d\u3046\u306a\u9805\u76ee\u304c\u4e26\u3093\u3067\u308b\u3093\u3067\u3059\u306d&#8230;<\/p>\n\n\n\n<p>\u3069\u3046\u3067\u3082\u3044\u3044\u3067\u3059\u304c\uff0c\u6559\u80b2\u6c34\u6e96\u306f\u533a\u5206\u304c\u3081\u3061\u3083\u3081\u3061\u3083\u7d30\u304b\u3044\u3067\u3059\u306d\uff08\u7b11\uff09<\/p>\n\n\n\n<h2>\u7c21\u5358\u306a\u8981\u7d04\u7d71\u8a08\u91cf<\/h2>\n\n\n\n<p>\n\n\u305b\u3063\u304b\u304f\u3067\u3059\u3057\uff0c\u8a18\u8ff0\u7d71\u8a08\u3057\u3066\u307f\u307e\u3057\u3087\u3046\uff01\n\n<\/p>\n\n\n\n<p>\u8981\u7d04\u7d71\u8a08\u91cf\u306fsummary()\u3067\u51fa\u305b\u307e\u3059\uff0e<\/p>\n\n\n\n<pre class=\"wp-block-luxe-blocks-syntaxhighlighter line-numbers language-r\"><code class=\"language-r\">summary(election)<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code>               MORALG                  CARESG   \n 1 Extremely well :423   1 Extremely well :277  \n 2 Quite well     :820   2 Quite well     :713  \n 3 Not too well   :287   3 Not too well   :464  \n 4 Not well at all:133   4 Not well at all:232  \n NA's             :122   NA's             : 99  \n                                                \n                                                \n               KNOWG                   LEADG    \n 1 Extremely well :461   1 Extremely well :258  \n 2 Quite well     :997   2 Quite well     :728  \n 3 Not too well   :212   3 Not too well   :522  \n 4 Not well at all: 59   4 Not well at all:185  \n NA's             : 56   NA's             : 92  \n                                                \n                                                \n              DISHONG                  INTELG   \n 1 Extremely well :133   1 Extremely well :494  \n 2 Quite well     :312   2 Quite well     :995  \n 3 Not too well   :629   3 Not too well   :182  \n 4 Not well at all:557   4 Not well at all: 65  \n NA's             :154   NA's             : 49  \n                                                \n                                                \n               MORALB                  CARESB   \n 1 Extremely well :340   1 Extremely well :155  \n 2 Quite well     :841   2 Quite well     :625  \n 3 Not too well   :330   3 Not too well   :562  \n 4 Not well at all: 98   4 Not well at all:342  \n NA's             :176   NA's             :101  \n                                                \n                                                \n               KNOWB                   LEADB    \n 1 Extremely well :274   1 Extremely well :266  \n 2 Quite well     :933   2 Quite well     :842  \n 3 Not too well   :379   3 Not too well   :407  \n 4 Not well at all:133   4 Not well at all:166  \n NA's             : 66   NA's             :104  \n                                                \n                                                \n              DISHONB                  INTELB        VOTE3      \n 1 Extremely well : 70   1 Extremely well :329   Min.   :1.000  \n 2 Quite well     :288   2 Quite well     :967   1st Qu.:1.000  \n 3 Not too well   :653   3 Not too well   :306   Median :1.000  \n 4 Not well at all:574   4 Not well at all:110   Mean   :1.534  \n NA's             :200   NA's             : 73   3rd Qu.:2.000  \n                                                 Max.   :3.000  \n                                                 NA's   :625    \n      AGE             EDUC           GENDER         PARTY      \n Min.   :18.00   Min.   :1.000   Min.   :1.00   Min.   :1.000  \n 1st Qu.:34.00   1st Qu.:3.000   1st Qu.:1.00   1st Qu.:2.000  \n Median :45.00   Median :4.000   Median :2.00   Median :3.000  \n Mean   :47.12   Mean   :4.305   Mean   :1.56   Mean   :3.726  \n 3rd Qu.:58.00   3rd Qu.:6.000   3rd Qu.:2.00   3rd Qu.:6.000  \n Max.   :97.00   Max.   :7.000   Max.   :2.00   Max.   :7.000  \n NA's   :9       NA's   :6                      NA's   :25  <\/code><\/pre>\n\n\n\n<h2>\u30b0\u30e9\u30d5\u5316\u3057\u307e\u3057\u3087<\/h2>\n\n\n\n<p>\u540c\u3058\u8a55\u4fa1\u9805\u76ee\u306b\u3064\u3044\u3066\uff0c\u30b4\u30a2\u3068\u30d6\u30c3\u30b7\u30e5\u3067\u6bd4\u8f03\u3057\u3066\u307f\u307e\u3057\u3087\u3046\uff0e<\/p>\n\n\n\n<p>\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u306e\u898b\u82e6\u3057\u3055\u306f\u7570\u5e38w<\/p>\n\n\n\n<pre class=\"wp-block-luxe-blocks-syntaxhighlighter line-numbers language-r\"><code class=\"language-r\">par(mfcol=c(6,2))\nbarplot(table(election$MORALG),  main=\"MORALG\",  ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$CARESG),  main=\"CARESG\",  ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$KNOWG),   main=\"KNOWG\",   ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$LEADG),   main=\"LEADG\",   ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$DISHONG), main=\"DISHONG\", ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$INTELG),  main=\"INTELG\",  ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$MORALB),  main=\"MORALB\",  ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$CARESB),  main=\"CARESB\",  ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$KNOWB),   main=\"KNOWB\",   ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$LEADB),   main=\"LEADB\",   ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$DISHONB), main=\"DISHONB\", ylab = \"count\", ylim = c(0,1000))\nbarplot(table(election$INTELB),  main=\"INTELB\",  ylab = \"count\", ylim = c(0,1000))<\/code><\/pre>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/ujicya.jp\/wordpress\/wp-content\/uploads\/2019\/07\/Rplot02-578x1024.png\" alt=\"\" class=\"wp-image-270\"\/><figcaption>\u56f3\uff11\u3000\u30b4\u30a2\uff08\u5de6\uff09\u3068\u30d6\u30c3\u30b7\u30e5\uff08\u53f3\uff09\u306e\u8a55\u4fa1<\/figcaption><\/figure>\n\n\n\n<p>\u3053\u306e\u56f3\uff11\u3092\u307f\u308b\u3068\uff0c\u3069\u306e\u9805\u76ee\u3082\u4e21\u8005\u3067\u5927\u5dee\u306a\u3044\u3088\u3046\u306b\u898b\u3048\u307e\u3059\u306d\uff0e<\/p>\n\n\n\n<p>\u3057\u304b\u3057\uff0c\u305d\u306e\u89e3\u91c8\u3067\u7d42\u3048\u3066\u306f\uff0c\u6f5c\u5728\u30af\u30e9\u30b9\u5206\u6790\u306b\u306a\u308a\u307e\u305b\u3093\uff01<\/p>\n\n\n\n<p>\u3053\u3053\u3067\u8003\u3048\u308b\u306e\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u3053\u306e\u30c7\u30fc\u30bf\u306f\uff0c\u8907\u6570\u306e\u6d3e\u95a5\uff08\u30af\u30e9\u30b9\uff09\u306e\u56de\u7b54\u30c7\u30fc\u30bf\u304c\u6df7\u5408\u3057\u3066\u3044\u308b\u306e\u3060\u3068\uff0e<\/p>\n\n\n\n<p>\u4f8b\u3048\u3070\uff0c\u30b4\u30a2\u6d3e\u3068\u30d6\u30c3\u30b7\u30e5\u6d3e\u306e2\u3064\u306e\u6d3e\u95a5\u3068\u304b\uff0c\u4e2d\u7acb\u306a\u4eba\u3082\u542b\u3081\u305f3\u3064\u306e\u6d3e\u95a5\u3068\u304b\u3067\u3059\uff0e<\/p>\n\n\n\n<p>\u3059\u308b\u3068\uff0c\u30b4\u30a2\u6d3e\u306e\u4eba\u306f\u30b4\u30a2\u306b\u80af\u5b9a\u7684\u306a\u8a55\u4fa1\u3092\u4e0e\u3048\uff0c\u30d6\u30c3\u30b7\u30e5\u306b\u5426\u5b9a\u7684\u306a\u8a55\u4fa1\u3092\u4e0e\u3048\u308b\u3068\u4e88\u60f3\u3067\u304d\u307e\u3059\uff0e<\/p>\n\n\n\n<p>\u9006\u3082\u307e\u305f\u3057\u304b\u308a\u3067\u3059\uff0e<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>\u3067\u306f\u6b21\u56de\u304b\u3089\uff0c\u5b9f\u969b\u306b\u6f5c\u5728\u30af\u30e9\u30b9\u5206\u6790\u3092\u3057\u3066\u3044\u304d\u307e\u3059\uff0e<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6f5c\u5728\u30af\u30e9\u30b9\u30e2\u30c7\u30eb\uff08Latent class model\uff09\u306f\uff0c\u7d71\u8a08\u30e2\u30c7\u30eb\u306e\u4e00\u7a2e\u3067\u3042\u308a\uff0c\u30a2\u30f3\u30b1\u30fc\u30c8\u8abf\u67fb\u306e\u5206\u6790\u306a\u3069\u306b\u4f7f\u308f\u308c\u307e\u3059\uff0e \u672c\u30e2\u30c7\u30eb\u3067\u306f\uff0c\u56de\u7b54\u8005\u304c\u7570\u306a\u308b\u50be\u5411\u3092\u6301\u3064\u8907\u6570\u306e\u96c6\u56e3\uff08\u30af\u30e9\u30b9\uff09\u306b\u3088\u3063\u3066\u69cb\u6210\u3055\u308c\u308b\u3068\u60f3\u5b9a\u3057\u307e\u3059\uff0e \u3064\u307e [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[18,20,33],"_links":{"self":[{"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/posts\/257"}],"collection":[{"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/comments?post=257"}],"version-history":[{"count":0,"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/posts\/257\/revisions"}],"wp:attachment":[{"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/media?parent=257"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/categories?post=257"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ujicya.jp\/blog-mapping\/wp-json\/wp\/v2\/tags?post=257"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}