{"id":3059,"date":"2023-07-19T09:36:46","date_gmt":"2023-07-19T09:36:46","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%95%e3%82%a3%e3%83%83%e3%82%b7%e3%83%a3%e3%83%bc%e3%83%9e%e3%83%b3%e3%82%b9%e3%82%99-lsd-in-r\/"},"modified":"2023-07-19T09:36:46","modified_gmt":"2023-07-19T09:36:46","slug":"%e3%83%95%e3%82%a3%e3%83%83%e3%82%b7%e3%83%a3%e3%83%bc%e3%83%9e%e3%83%b3%e3%82%b9%e3%82%99-lsd-in-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%95%e3%82%a3%e3%83%83%e3%82%b7%e3%83%a3%e3%83%bc%e3%83%9e%e3%83%b3%e3%82%b9%e3%82%99-lsd-in-r\/","title":{"rendered":"R \u3067\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6700\u5c0f\u6709\u610f\u5dee (lsd) \u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u4e00\u65b9\u5411\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001<\/a> 3 \u3064\u4ee5\u4e0a\u306e\u72ec\u7acb\u3057\u305f\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u9593\u306b\u7d71\u8a08\u7684\u306b\u6709\u610f\u306a\u5dee\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3067\u4f7f\u7528\u3055\u308c\u308b<a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">\u4eee\u5b9a\u306f<\/a>\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>H <sub>0<\/sub><\/strong> : \u5e73\u5747\u306f\u5404\u30b0\u30eb\u30fc\u30d7\u3067\u7b49\u3057\u3044\u3002<\/span><\/li>\n<li> <strong>H <sub style=\"color: #000000;\">A<\/sub><\/strong> <span style=\"color: #000000;\">: \u5c11\u306a\u304f\u3068\u3082 1 \u3064\u306e\u65b9\u6cd5\u306f\u4ed6\u306e\u65b9\u6cd5\u3068\u306f\u7570\u306a\u308a\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">ANOVA \u306e<a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">p \u5024\u304c<\/a>\u7279\u5b9a\u306e\u6709\u610f\u30ec\u30d9\u30eb (\u03b1 = 0.05 \u306a\u3069) \u3092\u4e0b\u56de\u3063\u3066\u3044\u308b\u5834\u5408\u3001\u5e30\u7121\u4eee\u8aac\u3092\u68c4\u5374\u3057\u3001\u30b0\u30eb\u30fc\u30d7\u5e73\u5747\u306e\u5c11\u306a\u304f\u3068\u3082 1 \u3064\u304c\u4ed6\u306e\u5e73\u5747\u3068\u306f\u7570\u306a\u308b\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3057\u304b\u3057\u3001\u3069\u306e\u30b0\u30eb\u30fc\u30d7\u304c\u4e92\u3044\u306b\u7570\u306a\u3063\u3066\u3044\u308b\u304b\u3092\u6b63\u78ba\u306b\u77e5\u308b\u306b\u306f\u3001\u4e8b\u5f8c\u30c6\u30b9\u30c8\u3092\u884c\u3046\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u7684\u306b\u4f7f\u7528\u3055\u308c\u308b\u4e8b\u5f8c\u691c\u5b9a\u306f<strong>\u3001\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6700\u5c0f\u6709\u610f\u5dee (LSD) \u691c\u5b9a<\/strong>\u3067\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>agricolae<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u306e<strong>LSD.test()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001R \u3067\u3053\u306e\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: R \u3067\u306e\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e LSD \u30c6\u30b9\u30c8<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6559\u6388\u304c\u30013 \u3064\u306e\u7570\u306a\u308b\u5b66\u7fd2\u65b9\u6cd5\u304c\u751f\u5f92\u9593\u3067\u30c6\u30b9\u30c8\u306e\u5f97\u70b9\u306b\u5dee\u3092\u3082\u305f\u3089\u3059\u304b\u3069\u3046\u304b\u3092\u77e5\u308a\u305f\u3044\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3092\u30c6\u30b9\u30c8\u3059\u308b\u305f\u3081\u306b\u3001\u5f7c\u5973\u306f 10 \u4eba\u306e\u751f\u5f92\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u5272\u308a\u5f53\u3066\u3066\u5404\u5b66\u7fd2\u624b\u6cd5\u3092\u4f7f\u7528\u3055\u305b\u3001\u8a66\u9a13\u7d50\u679c\u3092\u8a18\u9332\u3057\u307e\u3057\u305f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u8868\u306f\u3001<\/span><span style=\"color: #000000;\">\u4f7f\u7528\u3057\u305f\u5b66\u7fd2\u624b\u6cd5\u306b\u57fa\u3065\u3044\u305f\u5404\u751f\u5f92\u306e\u8a66\u9a13\u7d50\u679c\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-16018 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/moinssigdiff1.png\" alt=\"\" width=\"267\" height=\"287\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001R \u3067\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create data frame\n<span style=\"color: #000000;\">df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (technique = rep(c(\"tech1\", \"tech2\", \"tech3\"), each = <span style=\"color: #008000;\">10<\/span> ),\n                   score = c(72, 73, 73, 77, 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\n<\/span>head(df)\n\n  technical score\n1 tech1 72\n2 tech1 73\n3 tech1 73\n4 tech1 77\n5 tech1 82\n6 tech1 82\n\n<span style=\"color: #008080;\">#fit one-way ANOVA\n<\/span>model &lt;- aov(score ~ technique, data = df)\n\n<span style=\"color: #008080;\">#view summary of one-way ANOVA\n<\/span>summary(model)\n\n            Df Sum Sq Mean Sq F value Pr(&gt;F)  \ntechnical 2 341.6 170.80 4.623 0.0188 *\nResiduals 27,997.6 36.95                 \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">ANOVA \u8868\u306e p \u5024 (0.0188) \u306f 0.05 \u672a\u6e80\u3067\u3042\u308b\u305f\u3081\u30013 \u3064\u306e\u30b0\u30eb\u30fc\u30d7\u9593\u306e\u8a66\u9a13\u306e\u5e73\u5747\u5f97\u70b9\u306f\u3059\u3079\u3066\u7b49\u3057\u304f\u306a\u3044\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3057\u305f\u304c\u3063\u3066\u3001\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e LSD \u691c\u5b9a\u3092\u5b9f\u884c\u3057\u3066\u3001\u3069\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u5024\u304c\u7570\u306a\u308b\u304b\u3092\u5224\u65ad\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u3053\u308c\u3092\u884c\u3046\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;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">library<\/span> (agricolae)<\/span>\n\n#perform Fisher's LSD\n<span style=\"color: #000000;\">print( <span style=\"color: #3366ff;\">LSD.test<\/span> (model,\" <span style=\"color: #ff0000;\">technic<\/span> \"))\n            \n$statistics\n   MSerror Df Mean CV t.value LSD\n  36.94815 27 84.6 7.184987 2.051831 5.57767\n\n$parameters\n        test p.adjusted name.t ntr alpha\n  Fisher-LSD none technical 3 0.05\n\n$means\n      std score r LCL UCL Min Max Q25 Q50 Q75\ntech1 80.0 5.868939 10 76.05599 83.94401 72 89 74.00 82.0 83.75\ntech2 85.8 4.391912 10 81.85599 89.74401 81 93 83.00 83.5 89.25\ntech3 88.0 7.557189 10 84.05599 91.94401 77 98 81.25 89.5 94.00\n\n$comparison\nNULL\n\n$groups\n      score groups\ntech3 88.0 a\ntech2 85.8a\ntech1 80.0 b\n\nattr(,\"class\")\n[1] \u201cgroup\u201d\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u306e\u4e2d\u3067\u6700\u3082\u8208\u5473\u6df1\u3044\u90e8\u5206\u306f\u3001 <strong>$groups<\/strong>\u3068\u547c\u3070\u308c\u308b\u30bb\u30af\u30b7\u30e7\u30f3\u3067\u3059\u3002<strong>\u30b0\u30eb\u30fc\u30d7<\/strong>\u5217\u306b\u7570\u306a\u308b\u6587\u5b57\u304c\u542b\u307e\u308c\u308b\u30c6\u30af\u30cb\u30c3\u30af\u306f\u975e\u5e38\u306b\u7570\u306a\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u304b\u3089\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u30c6\u30af\u30cb\u30c3\u30af 1 \u3068\u30c6\u30af\u30cb\u30c3\u30af 3 \u306e\u5e73\u5747\u8a66\u9a13\u30b9\u30b3\u30a2\u306f\u5927\u304d\u304f\u7570\u306a\u308a\u307e\u3059 (tech1 \u306e\u5024\u306f\u300cb\u300d\u3001tech3 \u306e\u5024\u306f\u300ca\u300d\u3067\u3042\u308b\u305f\u3081)\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c6\u30af\u30cb\u30c3\u30af 1 \u3068\u30c6\u30af\u30cb\u30c3\u30af 2 \u306e\u5e73\u5747\u8a66\u9a13\u30b9\u30b3\u30a2\u306f\u5927\u304d\u304f\u7570\u306a\u308a\u307e\u3059 (tech1 \u306e\u5024\u306f\u300cb\u300d\u3001tech2 \u306e\u5024\u306f\u300ca\u300d\u3067\u3042\u308b\u305f\u3081)\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c6\u30af\u30cb\u30c3\u30af 2 \u3068\u30c6\u30af\u30cb\u30c3\u30af 3 \u306e\u5e73\u5747\u8a66\u9a13\u30b9\u30b3\u30a2\u306f\u5927\u304d\u304f<strong>\u7570\u306a\u308a\u307e\u305b\u3093<\/strong>(\u4e21\u65b9\u3068\u3082\u300ca\u300d\u5024\u3092\u6301\u3063\u3066\u3044\u308b\u305f\u3081)\u3002<\/span><\/li>\n<\/ul>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">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\/r\u306e\u30db\u3099\u30f3\u30d5\u30a7\u30ed\u30fc\u30cb\u88dc\u6b63\/\" target=\"_blank\" rel=\"noopener\">R \u3067 Bonferroni \u4e8b\u5f8c\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/r\u306e\u30c6\u30b9\u30c8\u30de\u30cd\u30fc\u30b7\u3099\u30e3\u30fc\/\" target=\"_blank\" rel=\"noopener\">R \u3067\u30b7\u30a7\u30c3\u30d5\u30a7\u4e8b\u5f8c\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001 3 \u3064\u4ee5\u4e0a\u306e\u72ec\u7acb\u3057\u305f\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u9593\u306b\u7d71\u8a08\u7684\u306b\u6709\u610f\u306a\u5dee\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002 \u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3067\u4f7f\u7528\u3055\u308c\u308b\u4eee\u5b9a\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002 H 0 : \u5e73\u5747\u306f\u5404\u30b0\u30eb\u30fc\u30d7\u3067\u7b49\u3057\u3044\u3002 H A 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