{"id":1041,"date":"2023-07-27T21:10:05","date_gmt":"2023-07-27T21:10:05","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%82%bf%e3%82%99%e3%83%8d%e3%83%83%e3%83%88%e3%83%86%e3%82%b9%e3%83%88r\/"},"modified":"2023-07-27T21:10:05","modified_gmt":"2023-07-27T21:10:05","slug":"%e3%82%bf%e3%82%99%e3%83%8d%e3%83%83%e3%83%88%e3%83%86%e3%82%b9%e3%83%88r","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%82%bf%e3%82%99%e3%83%8d%e3%83%83%e3%83%88%e3%83%86%e3%82%b9%e3%83%88r\/","title":{"rendered":"R \u3067\u30c0\u30cd\u30c3\u30c8\u306e\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u4e8b\u5f8c\u5206\u6563\u5206\u6790\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e8b\u5f8c\u691c\u5b9a\u306f\u3001<\/a>\u3069\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u5024\u304c\u4e92\u3044\u306b\u7d71\u8a08\u7684\u306b\u6709\u610f\u306b\u7570\u306a\u308b\u304b\u3092\u6c7a\u5b9a\u3059\u308b\u305f\u3081\u306b\u3001 <a href=\"https:\/\/statorials.org\/ja\/\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener noreferrer\">ANOVA<\/a>\u306e\u5f8c\u306b\u5b9f\u884c\u3055\u308c\u308b\u691c\u5b9a\u306e\u4e00\u7a2e\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7814\u7a76\u30b0\u30eb\u30fc\u30d7\u306e 1 \u3064\u304c<em>\u5bfe\u7167\u30b0\u30eb\u30fc\u30d7<\/em>\u3068\u307f\u306a\u3055\u308c\u308b\u5834\u5408\u306f\u3001 <a href=\"https:\/\/statorials.org\/ja\/\u30bf\u3099\u30cd\u30c3\u30c8\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u30c0\u30cd\u30c3\u30c8\u306e\u691c\u5b9a\u3092<\/a>\u4e8b\u5f8c\u691c\u5b9a\u3068\u3057\u3066\u4f7f\u7528\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u30c0\u30cd\u30c3\u30c8 \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: R \u3067\u306e\u30c0\u30cd\u30c3\u30c8 \u30c6\u30b9\u30c8<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6559\u5e2b\u304c 2 \u3064\u306e\u65b0\u3057\u3044\u5b66\u7fd2\u30c6\u30af\u30cb\u30c3\u30af\u304c\u751f\u5f92\u306e\u30c6\u30b9\u30c8\u306e\u6210\u7e3e\u3092\u5411\u4e0a\u3055\u305b\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u77e5\u308a\u305f\u3044\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u3057\u307e\u3059\u3002\u3053\u308c\u3092\u30c6\u30b9\u30c8\u3059\u308b\u305f\u3081\u306b\u3001\u5f7c\u5973\u306f 30 \u4eba\u306e\u751f\u5f92\u306e\u30af\u30e9\u30b9\u3092\u6b21\u306e 3 \u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u30e9\u30f3\u30c0\u30e0\u306b\u5206\u5272\u3057\u307e\u3057\u305f\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5bfe\u7167\u7fa4: 10 \u4eba\u306e\u5b66\u751f<\/span><\/li>\n<li><span style=\"color: #000000;\">\u65b0\u3057\u3044\u6280\u8853\u5b66\u7fd2 1: \u5b66\u751f 10 \u540d<\/span><\/li>\n<li><span style=\"color: #000000;\">\u65b0\u6280\u8853\u5b66\u7fd22\uff1a10\u540d<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5272\u308a\u5f53\u3066\u3089\u308c\u305f\u5b66\u7fd2\u65b9\u6cd5\u3092 1 \u9031\u9593\u4f7f\u7528\u3057\u305f\u5f8c\u3001\u5404\u751f\u5f92\u306f\u540c\u3058\u8a66\u9a13\u3092\u53d7\u3051\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">R \u3067\u6b21\u306e\u624b\u9806\u3092\u4f7f\u7528\u3057\u3066\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u30b0\u30eb\u30fc\u30d7\u5e73\u5747\u3092\u8996\u899a\u5316\u3057\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3057\u3001\u6700\u5f8c\u306b\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u3092\u5b9f\u884c\u3057\u3066\u3001\u3069\u306e\u65b0\u3057\u3044\u7814\u7a76\u624b\u6cd5 (\u5b58\u5728\u3059\u308b\u5834\u5408) \u304c\u5bfe\u7167\u30b0\u30eb\u30fc\u30d7\u3068\u6bd4\u8f03\u3057\u3066\u7570\u306a\u308b\u7d50\u679c\u3092\u751f\u307f\u51fa\u3059\u304b\u3092\u5224\u65ad\u3067\u304d\u307e\u3059\u3002 \u3002<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u30b9\u30c6\u30c3\u30d7 1: \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u300130 \u4eba\u306e\u5b66\u751f\u5168\u54e1\u306e\u8a66\u9a13\u7d50\u679c\u3092\u542b\u3080\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create data frame<\/span>\ndata &lt;- data.frame(technique = <span style=\"color: #3366ff;\">rep<\/span> (c(\"control\", \"new1\", \"new2\"), <span style=\"color: #3366ff;\">each<\/span> = <span style=\"color: #008000;\">10<\/span> ),\n                   score = c(76, 77, 77, 81, 82, 82, 83, 84, 85, 89,\n                             81, 82, 83, 83, 83, 84, 87, 90, 92, 93,\n                             77, 78, 79, 88, 89, 90, 91, 95, 95, 98))\n\n<span style=\"color: #008080;\">#view first six rows of data frame<\/span>\nhead(data)\n\n  technical score\n1 control 76\n2 controls 77\n3 controls 77\n4 controls 81\n5 controls 82\n6 controls 82\n<\/strong><\/pre>\n<p><strong><span style=\"color: #000000;\">\u30b9\u30c6\u30c3\u30d7 2: \u5404\u30b0\u30eb\u30fc\u30d7\u306e\u8a66\u9a13\u7d50\u679c\u3092\u8868\u793a\u3057\u307e\u3059\u3002<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u7bb1\u3072\u3052\u56f3\u3092\u4f5c\u6210\u3057\u3066\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u691c\u67fb\u7d50\u679c\u306e\u5206\u5e03\u3092\u8996\u899a\u5316\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>boxplot(score ~ technique,\n        data = data,\n        main = \"Exam Scores by Studying Technique\",\n        xlab = \"Studying Technique\",\n        ylab = \"Exam Scores\",\n        col = \"steelblue\",\n        border = \"black\")\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-10788 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/dunnettsr.png\" alt=\"\" width=\"378\" height=\"369\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u7bb1\u3072\u3052\u56f3\u304b\u3089\u3060\u3051\u3067\u3082\u3001\u8a66\u9a13\u306e\u5f97\u70b9\u306e\u5206\u5e03\u304c\u5b66\u7fd2\u624b\u6cd5\u3054\u3068\u306b\u5927\u304d\u304f\u7570\u306a\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u6b21\u306b\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3057\u3066\u3001\u3053\u308c\u3089\u306e\u9055\u3044\u304c\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u95a2\u9023:<\/strong> <a href=\"https:\/\/statorials.org\/ja\/\u8907\u6570\u306e\u7bb1\u3072\u3051\u3099\u56f3r\/\" target=\"_blank\" rel=\"noopener noreferrer\">R \u3067\u5358\u4e00\u306e\u30b0\u30e9\u30d5\u306b\u8907\u6570\u306e\u7bb1\u3072\u3052\u56f3\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5<\/a><\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u30b9\u30c6\u30c3\u30d7 3: \u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3057\u3066\u3001\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u8a66\u9a13\u5f97\u70b9\u9593\u306e\u5dee\u7570\u3092\u30c6\u30b9\u30c8\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit the one-way ANOVA model<\/span>\nmodel &lt;- aov(score ~ technique, data = data)\n\n<span style=\"color: #008080;\">#view model output\n<\/span>summary(model)\n\n            Df Sum Sq Mean Sq F value Pr(&gt;F)  \ntechnical 2 211.5 105.73 3.415 0.0476 *\nResiduals 27 836.0 30.96                 \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5168\u4f53\u306e p \u5024 ( <strong>0.0476<\/strong> ) \u306f 0.05 \u672a\u6e80\u3067\u3042\u308b\u305f\u3081\u3001\u3053\u308c\u306f\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u8a66\u9a13\u5e73\u5747\u70b9\u304c\u540c\u3058\u3067\u306f\u306a\u3044\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002\u6b21\u306b\u3001\u30c0\u30cd\u30c3\u30c8 \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u3066\u3001\u3069\u306e\u52c9\u5f37\u6cd5\u304c\u5bfe\u7167\u7fa4\u3068\u7570\u306a\u308b\u8a66\u9a13\u306e\u5e73\u5747\u70b9\u3092\u3082\u305f\u3089\u3057\u305f\u304b\u3092\u5224\u65ad\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u30b9\u30c6\u30c3\u30d7 4: \u30c0\u30cd\u30c3\u30c8 \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\">R \u3067 Dunnett \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3059\u308b<strong>DescTools<\/strong>\u30e9\u30a4\u30d6\u30e9\u30ea\u306e<strong>DunnettTest()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<blockquote>\n<p><span style=\"color: #000000;\"><strong>\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a(x, g)<\/strong><\/span><\/p>\n<\/blockquote>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x:<\/strong>\u30c7\u30fc\u30bf\u5024\u306e\u6570\u5024\u30d9\u30af\u30c8\u30eb (\u8a66\u9a13\u7d50\u679c\u306a\u3069)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>g:<\/strong>\u30b0\u30eb\u30fc\u30d7\u306e\u540d\u524d\u3092\u6307\u5b9a\u3059\u308b\u30d9\u30af\u30c8\u30eb (\u4f8b: \u5b66\u7fd2\u30c6\u30af\u30cb\u30c3\u30af)<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u3053\u306e\u4f8b\u3067\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load DescTools library<\/span>\nlibrary(DescTools)\n\n<span style=\"color: #008080;\">#perform Dunnett's Test\n<\/span>DunnettTest(x=data$score, g=data$technique)\n\n  Dunnett's test for comparing several treatments with a control:  \n    95% family-wise confidence level\n\n$control\n             diff lwr.ci upr.ci pval    \nnew1-control 4.2 -1.6071876 10.00719 0.1787    \nnew2-control 6.4 0.5928124 12.20719 0.0296 *  \n\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1' '1.' 0.1 ' ' 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u65b0\u3057\u3044\u52c9\u5f37\u6cd5 1 \u3068\u5bfe\u7167\u7fa4\u306e\u8a66\u9a13\u5f97\u70b9\u306e\u5e73\u5747\u5dee\u306f<strong>4.2 \u3067\u3057\u305f\u3002<\/strong>\u5bfe\u5fdc\u3059\u308b p \u5024\u306f<strong>0.1787<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u65b0\u3057\u3044\u52c9\u5f37\u6cd5 2 \u3068\u5bfe\u7167\u7fa4\u306e\u8a66\u9a13\u5f97\u70b9\u306e\u5e73\u5747\u5dee\u306f<strong>6.4 \u3067\u3057\u305f\u3002<\/strong>\u5bfe\u5fdc\u3059\u308b p \u5024\u306f<strong>0.0296<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u306b\u57fa\u3065\u3044\u3066\u3001\u30c6\u30af\u30cb\u30c3\u30af 2 \u306e\u5b66\u7fd2\u304c\u3001\u5bfe\u7167\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u30b9\u30b3\u30a2\u3068\u6709\u610f\u306b (p = 0.0296) \u7570\u306a\u308b\u5e73\u5747\u8a66\u9a13\u30b9\u30b3\u30a2\u3092\u751f\u307f\u51fa\u3059\u552f\u4e00\u306e\u30c6\u30af\u30cb\u30c3\u30af\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/\u4e00\u65b9\u5411\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306e\u6982\u8981<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener noreferrer\">R \u3067\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30c6\u30e5\u30fc\u30ad\u30fc\u30c6\u30b9\u30c8r\/\" target=\"_blank\" rel=\"noopener noreferrer\">R \u3067 Tukey \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e8b\u5f8c\u691c\u5b9a\u306f\u3001\u3069\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u5024\u304c\u4e92\u3044\u306b\u7d71\u8a08\u7684\u306b\u6709\u610f\u306b\u7570\u306a\u308b\u304b\u3092\u6c7a\u5b9a\u3059\u308b\u305f\u3081\u306b\u3001 ANOVA\u306e\u5f8c\u306b\u5b9f\u884c\u3055\u308c\u308b\u691c\u5b9a\u306e\u4e00\u7a2e\u3067\u3059\u3002 \u7814\u7a76\u30b0\u30eb\u30fc\u30d7\u306e 1 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