{"id":512,"date":"2018-08-18T10:15:54","date_gmt":"2018-08-18T01:15:54","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/multiple-comparison-of-means-with-covariates-adjustment\/"},"modified":"2024-10-13T19:10:25","modified_gmt":"2024-10-13T10:10:25","slug":"multiple-comparison-of-means-with-covariates-adjustment","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/multiple-comparison-of-means-with-covariates-adjustment\/","title":{"rendered":"R \u3067 \u5171\u5206\u6563\u5206\u6790\u306b\u304a\u3044\u3066 3 \u7fa4\u4ee5\u4e0a\u306e\u30ab\u30c6\u30b4\u30ea\u306e\u591a\u91cd\u6bd4\u8f03\u3092\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"\n<p>\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u591a\u91cd\u6bd4\u8f03\u3057\u305f\u3044\u3002<\/p>\n\n\n\n<p>\u3067\u3082\u5404\u7fa4\u306e\u80cc\u666f\u56e0\u5b50\u304c\u305d\u308d\u3063\u3066\u3044\u306a\u3044\u3002<\/p>\n\n\n\n<p>\u80cc\u666f\u56e0\u5b50\u3092\u8abf\u6574\u3057\u306a\u304c\u3089\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\u3069\u3046\u3059\u308c\u3070\u3044\u3044\u304b\uff1f<\/p>\n\n\n\n<p>R \u3067\u306e\u3084\u308a\u65b9\u3092\u89e3\u8aac\u3059\u308b\u3002<\/p>\n\n\n\n<!--more-->\n\n\n\n<h2 class=\"wp-block-heading\" id=\"\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u65b9\u6cd5\">\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u65b9\u6cd5<\/h2>\n\n\n\n<p>\u7fa4\u3054\u3068\u306e\u80cc\u666f\u56e0\u5b50\u306f\u3001\u7fa4\u5206\u3051\u5909\u6570\u3068\u4e00\u7dd2\u306b\u5909\u308f\u308b\u91cf\uff08\u5909\u6570\uff09\u306a\u306e\u3067\u3001\u5171\u5909\u91cf\uff08\u304d\u3087\u3046\u3078\u3093\u308a\u3087\u3046\uff09\u3068\u547c\u3076\u3002<\/p>\n\n\n\n<p>\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u306a\u304c\u3089\u591a\u91cd\u6bd4\u8f03\u3057\u3066\u307f\u308b\u3002<\/p>\n\n\n\n<p>\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u306a\u3044\u591a\u91cd\u6bd4\u8f03\u306f\u4e0b\u8a18\u53c2\u7167\u3002<\/p>\n\n\n<div class=\"swell-block-postLink\">\t\t\t<div class=\"p-blogCard -internal\" data-type=\"type1\" data-onclick=\"clickLink\">\n\t\t\t\t<div class=\"p-blogCard__inner\">\n\t\t\t\t\t<span class=\"p-blogCard__caption\">\u3042\u308f\u305b\u3066\u8aad\u307f\u305f\u3044<\/span>\n\t\t\t\t\t<div class=\"p-blogCard__thumb c-postThumb\"><figure class=\"c-postThumb__figure\"><img decoding=\"async\" src=\"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example_warpbreak-300x300.png\" alt=\"\" class=\"c-postThumb__img u-obf-cover\" width=\"320\" height=\"180\"><\/figure><\/div>\t\t\t\t\t<div class=\"p-blogCard__body\">\n\t\t\t\t\t\t<a class=\"p-blogCard__title\" href=\"https:\/\/best-biostatistics.com\/toukei-er\/entry\/how-to-do-tukey-test\/\">R \u3067\u30c1\u30e5\u30fc\u30ad\u30fc\u691c\u5b9a\u3092\u884c\u3046\u65b9\u6cd5<\/a>\n\t\t\t\t\t\t<span class=\"p-blogCard__excerpt\">Tukey HSD\u691c\u5b9a\u3092R\u3067\u884c\u3046\u65b9\u6cd5\u306e\u89e3\u8aac\u3002 Tukey HSD\u691c\u5b9a\u3092R\u3067\u884c\u3046\u65b9\u6cd5 aov()\u3068TukeyHSD()\u3068\u3044\u3046\u4e8c\u3064\u306e\u95a2\u6570\u3092\u4f7f\u3046\u3002 \u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u306e\u3068\u304d\u3068\u540c\u3058\u3088\u3046\u306b\u3001\u4f8b\u3068\u3057\u3066warpbreaks\u3068&#8230;<\/span>\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\n<div class=\"swell-block-postLink\">\t\t\t<div class=\"p-blogCard -internal\" data-type=\"type1\" data-onclick=\"clickLink\">\n\t\t\t\t<div class=\"p-blogCard__inner\">\n\t\t\t\t\t<span class=\"p-blogCard__caption\">\u3042\u308f\u305b\u3066\u8aad\u307f\u305f\u3044<\/span>\n\t\t\t\t\t<div class=\"p-blogCard__thumb c-postThumb\"><figure class=\"c-postThumb__figure\"><img decoding=\"async\" src=\"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example_warpbreak-1-300x300.png\" alt=\"\" class=\"c-postThumb__img u-obf-cover\" width=\"320\" height=\"180\"><\/figure><\/div>\t\t\t\t\t<div class=\"p-blogCard__body\">\n\t\t\t\t\t\t<a class=\"p-blogCard__title\" href=\"https:\/\/best-biostatistics.com\/toukei-er\/entry\/dunnett-test-in-r\/\">R \u3067\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u3092\u884c\u3046\u65b9\u6cd5<\/a>\n\t\t\t\t\t\t<span class=\"p-blogCard__excerpt\">\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u306f\u3001\u6bd4\u8f03\u5bfe\u7167\u7fa4\u3068\u3044\u304f\u3064\u304b\u306e\u5b9f\u9a13\u7fa4\u3092\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u65b9\u6cd5\u3002 R\u3067\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u3092\u3059\u308b\u306b\u306f\u3069\u3046\u3057\u305f\u3089\u3088\u3044\u304b\uff1f R\u3067\u30c0\u30cd\u30c3\u30c8\u691c\u5b9a\u3092\u3059\u308b\u306b\u306f\uff1f \u307e\u305amultcomp\u30d1\u30c3\u30b1\u30fc&#8230;<\/span>\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\n\n\n\n\n\n<h2 class=\"wp-block-heading\" id=\"\u4f7f\u7528\u3059\u308b\u30c7\u30fc\u30bf\">\u4f7f\u7528\u3059\u308b\u30c7\u30fc\u30bf<\/h2>\n\n\n\n<p>\u4eca\u56de\u4f8b\u306b\u4f7f\u3046\u306e\u306fmultcomp\u30d1\u30c3\u30b1\u30fc\u30b8\u306elitter\u3068\u3044\u3046\u30c7\u30fc\u30bf\u3002<\/p>\n\n\n\n<p>\u751f\u307e\u308c\u305f\u4ed4\u30e9\u30c3\u30c8\u5168\u4f53\u306e\u4f53\u91cd\u3092\u56db\u3064\u306e\u7528\u91cf\u7fa4\u3067\u6bd4\u8f03\u3059\u308b\u3002<\/p>\n\n\n\n<p>\u5171\u5909\u91cf\u306f\u3001\u51fa\u7523\u307e\u3067\u306e\u598a\u5a20\u65e5\u6570\u3068\u751f\u307e\u308c\u305f\u4ed4\u30e9\u30c3\u30c8\u306e\u6570\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><span class=\"synPreProc\">library<\/span><span class=\"synSpecial\">(<\/span>multcomp<span class=\"synSpecial\">)<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>litter<span class=\"synSpecial\">)<\/span>\n<span class=\"synIdentifier\">boxplot<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">,<\/span> xlab<span class=\"synStatement\">=<\/span><span class=\"synConstant\">\"Dose\"<\/span><span class=\"synSpecial\">,<\/span> ylab<span class=\"synStatement\">=<\/span><span class=\"synConstant\">\"Weight\"<\/span><span class=\"synSpecial\">)<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\n<span class=\"synIdentifier\">round<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">cor<\/span><span class=\"synSpecial\">(<\/span>litter<span class=\"synSpecial\">&#91;,<\/span><span class=\"synStatement\">-<\/span><span class=\"synConstant\">1<\/span><span class=\"synSpecial\">]),<\/span><span class=\"synConstant\">3<\/span><span class=\"synSpecial\">)<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>gesttime <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>number <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\n<\/code><\/pre>\n\n\n\n<p>\u30c7\u30fc\u30bf\u306e\u6982\u8981\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u51e6\u7f6e\u7528\u91cf\u306f0\u3001\uff15\u300150\u3001500\u306e\u56db\u7fa4\u300217\u4f8b\u304b\u308920\u4f8b\u3002<\/li>\n\n\n\n<li>\u4ed4\u30e9\u30c3\u30c8\u5168\u4f53\u306e\u4f53\u91cd\u306e\u5e73\u5747\u306f30.33\u30b0\u30e9\u30e0\u3002<\/li>\n\n\n\n<li>\u598a\u5a20\u671f\u9593\u306f\u3001\u5e73\u574722.09\u65e5\u3002<\/li>\n\n\n\n<li>\u5e73\u5747\u4ed4\u30e9\u30c3\u30c8\u6570\u306f13.43\u5339\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u4e0b\u8a18\u306f\u51e6\u7f6e\u7528\u91cf\u3068\u4f53\u91cd\u306e\u7bb1\u3072\u3052\u56f3\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"672\" height=\"672\" src=\"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example.png\" alt=\"\" class=\"wp-image-2806\" srcset=\"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example.png 672w, https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example-300x300.png 300w, https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example-150x150.png 150w\" sizes=\"(max-width: 672px) 100vw, 672px\" \/><\/figure>\n\n\n\n\n\n\n\n<p>\u307e\u305f\u3001ANOVA\u3084\u76f8\u95a2\u4fc2\u6570\u306a\u3069\u5358\u5909\u91cf\u89e3\u6790\u3067\u306f\u3001\u3069\u306e\u5909\u6570\u9593\u306b\u3082\u5f37\u3044\u95a2\u9023\u6027\u306f\u898b\u3089\u308c\u306a\u3044\u3053\u3068\u304c\u308f\u304b\u308b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><span class=\"synStatement\">&gt;<\/span> <span class=\"synPreProc\">library<\/span><span class=\"synSpecial\">(<\/span>multcomp<span class=\"synSpecial\">)<\/span>\n<span class=\"synStatement\">&gt;<\/span>\n<span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>litter<span class=\"synSpecial\">)<\/span>\ndose        weight         gesttime         number\n<span class=\"synConstant\">0<\/span>  <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">20<\/span>   Min.   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">19.22<\/span>   Min.   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">21.50<\/span>   Min.   <span class=\"synSpecial\">:<\/span> <span class=\"synConstant\">5.00<\/span>\n<span class=\"synConstant\">5<\/span>  <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">19<\/span>   1st Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">27.77<\/span>   1st Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">21.50<\/span>   1st Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">12.00<\/span>\n<span class=\"synConstant\">50<\/span> <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">18<\/span>   Median <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">30.76<\/span>   Median <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">22.00<\/span>   Median <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">14.00<\/span>\n<span class=\"synConstant\">500<\/span><span class=\"synSpecial\">:<\/span><span class=\"synConstant\">17<\/span>   Mean   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">30.33<\/span>   Mean   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">22.09<\/span>   Mean   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">13.43<\/span>\n3rd Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">33.30<\/span>   3rd Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">22.50<\/span>   3rd Qu.<span class=\"synSpecial\">:<\/span><span class=\"synConstant\">15.00<\/span>\nMax.   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">38.75<\/span>   Max.   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">23.00<\/span>   Max.   <span class=\"synSpecial\">:<\/span><span class=\"synConstant\">17.00<\/span>\n<span class=\"synStatement\">&gt;<\/span>\n<span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\nDf Sum Sq Mean Sq <span class=\"synConstant\">F<\/span> value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;<\/span><span class=\"synConstant\">F<\/span><span class=\"synSpecial\">)<\/span>\ndose         <span class=\"synConstant\">3<\/span>  <span class=\"synConstant\">109.9<\/span>   <span class=\"synConstant\">36.64<\/span>   <span class=\"synConstant\">1.954<\/span>  <span class=\"synConstant\">0.129<\/span>\nResiduals   <span class=\"synConstant\">70<\/span> <span class=\"synConstant\">1312.8<\/span>   <span class=\"synConstant\">18.75<\/span>\n<span class=\"synStatement\">&gt;<\/span>\n<span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">round<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">cor<\/span><span class=\"synSpecial\">(<\/span>litter<span class=\"synSpecial\">&#91;,<\/span><span class=\"synStatement\">-<\/span><span class=\"synConstant\">1<\/span><span class=\"synSpecial\">]),<\/span><span class=\"synConstant\">3<\/span><span class=\"synSpecial\">)<\/span>\nweight gesttime number\nweight    <span class=\"synConstant\">1.000<\/span>    <span class=\"synConstant\">0.307<\/span>  <span class=\"synConstant\">0.221<\/span>\ngesttime  <span class=\"synConstant\">0.307<\/span>    <span class=\"synConstant\">1.000<\/span> <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.046<\/span>\nnumber    <span class=\"synConstant\">0.221<\/span>   <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.046<\/span>  <span class=\"synConstant\">1.000<\/span>\n<span class=\"synStatement\">&gt;<\/span>\n<span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>gesttime <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\nDf Sum Sq Mean Sq <span class=\"synConstant\">F<\/span> value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;<\/span><span class=\"synConstant\">F<\/span><span class=\"synSpecial\">)<\/span>\ndose         <span class=\"synConstant\">3<\/span>  <span class=\"synConstant\">1.135<\/span>  <span class=\"synConstant\">0.3784<\/span>   <span class=\"synConstant\">2.031<\/span>  <span class=\"synConstant\">0.117<\/span>\nResiduals   <span class=\"synConstant\">70<\/span> <span class=\"synConstant\">13.044<\/span>  <span class=\"synConstant\">0.1863<\/span>\n<span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span><span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>number <span class=\"synStatement\">~<\/span> dose<span class=\"synSpecial\">,<\/span> data<span class=\"synStatement\">=<\/span>litter<span class=\"synSpecial\">))<\/span>\nDf Sum Sq Mean Sq <span class=\"synConstant\">F<\/span> value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;<\/span><span class=\"synConstant\">F<\/span><span class=\"synSpecial\">)<\/span>\ndose         <span class=\"synConstant\">3<\/span>   <span class=\"synConstant\">43.3<\/span>   <span class=\"synConstant\">14.45<\/span>   <span class=\"synConstant\">2.315<\/span> <span class=\"synConstant\">0.0833<\/span> .\nResiduals   <span class=\"synConstant\">70<\/span>  <span class=\"synConstant\">436.8<\/span>    <span class=\"synConstant\">6.24<\/span>\n<span class=\"synStatement\">---<\/span>\nSignif. codes<span class=\"synSpecial\">:<\/span>  <span class=\"synConstant\">0<\/span> \u2018<span class=\"synError\">***<\/span>\u2019 <span class=\"synConstant\">0.001<\/span> \u2018<span class=\"synStatement\">**<\/span>\u2019 <span class=\"synConstant\">0.01<\/span> \u2018<span class=\"synStatement\">*<\/span>\u2019 <span class=\"synConstant\">0.05<\/span> \u2018.\u2019 <span class=\"synConstant\">0.1<\/span> \u2018 \u2019 <span class=\"synConstant\">1<\/span>\n<\/code><\/pre>\n\n\n\n<div id=\"biost-2455575846\" 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\" id=\"\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30c1\u30e5\u30fc\u30ad\u30fc\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\">\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30c1\u30e5\u30fc\u30ad\u30fc\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\uff1f<\/h2>\n\n\n\n<p>\u598a\u5a20\u65e5\u6570\u3068\u4ed4\u30e9\u30c3\u30c8\u306e\u6570\u3092\u8abf\u6574\u3057\u306a\u304c\u3089\u3001\u4ed4\u30e9\u30c3\u30c8\u5168\u4f53\u306e\u4f53\u91cd\u3092\u56db\u7528\u91cf\u7fa4\u3067\u591a\u91cd\u6bd4\u8f03\u3002<\/p>\n\n\n\n<p>ANOVA\u306e\u95a2\u6570aov()\u3068\u591a\u91cd\u6bd4\u8f03\u306e\u95a2\u6570glht()\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>amod <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nglht.res.t <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">glht<\/span><span class=\"synSpecial\">(<\/span>amod<span class=\"synSpecial\">,<\/span> linfct <span class=\"synStatement\">=<\/span> <span class=\"synIdentifier\">mcp<\/span><span class=\"synSpecial\">(<\/span>dose <span class=\"synStatement\">=<\/span> <span class=\"synConstant\">\"Tukey\"<\/span><span class=\"synSpecial\">))<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.t<span class=\"synSpecial\">)<\/span>\n<\/code><\/pre>\n\n\n\n<p>\u7d50\u679c\u306f\u3001\u3069\u306e\u7fa4\u9593\u306b\u3082\u7d71\u8a08\u5b66\u7684\u6709\u610f\u5dee\u306a\u3057\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.t<span class=\"synSpecial\">)<\/span>\nSimultaneous Tests <span class=\"synStatement\">for<\/span> General Linear Hypotheses\nMultiple Comparisons of Means<span class=\"synSpecial\">:<\/span> Tukey Contrasts\nFit<span class=\"synSpecial\">:<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>formula <span class=\"synStatement\">=<\/span> weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nLinear Hypotheses<span class=\"synSpecial\">:<\/span>\nEstimate Std. Error t value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;|<\/span>t<span class=\"synStatement\">|<\/span><span class=\"synSpecial\">)<\/span>\n<span class=\"synConstant\">5<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>     <span class=\"synStatement\">-<\/span><span class=\"synConstant\">3.3524<\/span>     <span class=\"synConstant\">1.2908<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.597<\/span>   <span class=\"synConstant\">0.0546<\/span> .\n<span class=\"synConstant\">50<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>    <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.2909<\/span>     <span class=\"synConstant\">1.3384<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">1.712<\/span>   <span class=\"synConstant\">0.3251<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>   <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.6752<\/span>     <span class=\"synConstant\">1.3343<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.005<\/span>   <span class=\"synConstant\">0.1958<\/span>\n<span class=\"synConstant\">50<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">5<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>     <span class=\"synConstant\">1.0615<\/span>     <span class=\"synConstant\">1.3973<\/span>   <span class=\"synConstant\">0.760<\/span>   <span class=\"synConstant\">0.8719<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">5<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>    <span class=\"synConstant\">0.6772<\/span>     <span class=\"synConstant\">1.3394<\/span>   <span class=\"synConstant\">0.506<\/span>   <span class=\"synConstant\">0.9574<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">50<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.3844<\/span>     <span class=\"synConstant\">1.4510<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.265<\/span>   <span class=\"synConstant\">0.9934<\/span>\n<span class=\"synStatement\">---<\/span>\nSignif. codes<span class=\"synSpecial\">:<\/span>  <span class=\"synConstant\">0<\/span> \u2018<span class=\"synError\">***<\/span>\u2019 <span class=\"synConstant\">0.001<\/span> \u2018<span class=\"synStatement\">**<\/span>\u2019 <span class=\"synConstant\">0.01<\/span> \u2018<span class=\"synStatement\">*<\/span>\u2019 <span class=\"synConstant\">0.05<\/span> \u2018.\u2019 <span class=\"synConstant\">0.1<\/span> \u2018 \u2019 <span class=\"synConstant\">1<\/span>\n<span class=\"synSpecial\">(<\/span>Adjusted p values reported <span class=\"synStatement\">--<\/span> single<span class=\"synStatement\">-<\/span>step method<span class=\"synSpecial\">)<\/span>\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30c0\u30cd\u30c3\u30c8\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\">\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30c0\u30cd\u30c3\u30c8\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\uff1f<\/h2>\n\n\n\n<p>\u30c0\u30cd\u30c3\u30c8\u306e\u65b9\u6cd5\u306f\u3069\u3046\u3084\u308b\u304b\uff1f<\/p>\n\n\n\n<p>dose=&#8221;Tukey&#8221;\u306e\u3068\u3053\u308d\u3092dose=&#8221;Dunnett&#8221;\u306b\u5909\u3048\u308b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>amod <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nglht.res.d <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">glht<\/span><span class=\"synSpecial\">(<\/span>amod<span class=\"synSpecial\">,<\/span> linfct <span class=\"synStatement\">=<\/span> <span class=\"synIdentifier\">mcp<\/span><span class=\"synSpecial\">(<\/span>dose <span class=\"synStatement\">=<\/span> <span class=\"synConstant\">\"Dunnett\"<\/span><span class=\"synSpecial\">))<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.d<span class=\"synSpecial\">)<\/span>\n<\/code><\/pre>\n\n\n\n<p>\u30c0\u30cd\u30c3\u30c8\u306e\u65b9\u6cd5\u306f\u3001\u51e6\u7f6e\u7528\u91cf0\u7fa4\u3092\u5bfe\u7167\u3068\u3057\u3066\u6bd4\u8f03\u3059\u308b\u3002<\/p>\n\n\n\n<p>\u4eca\u56de\u306f5\u30680\u306e\u9593\u304c\u7d71\u8a08\u5b66\u7684\u6709\u610f\u3002<\/p>\n\n\n\n<p>\u3069\u3046\u8003\u3048\u3066\u30c7\u30b6\u30a4\u30f3\u3057\u3066\u3001\u3069\u3046\u89e3\u6790\u3057\u305f\u3044\u304b\u306b\u3088\u3063\u3066\u3001\u9078\u3076\u65b9\u6cd5\u304c\u5909\u308f\u308a\u3001\u7d71\u8a08\u5b66\u7684\u6709\u610f\u304b\u3069\u3046\u304b\u3082\u5909\u308f\u3063\u3066\u304f\u308b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.d<span class=\"synSpecial\">)<\/span>\nSimultaneous Tests <span class=\"synStatement\">for<\/span> General Linear Hypotheses\nMultiple Comparisons of Means<span class=\"synSpecial\">:<\/span> Dunnett Contrasts\nFit<span class=\"synSpecial\">:<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>formula <span class=\"synStatement\">=<\/span> weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nLinear Hypotheses<span class=\"synSpecial\">:<\/span>\nEstimate Std. Error t value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;|<\/span>t<span class=\"synStatement\">|<\/span><span class=\"synSpecial\">)<\/span>\n<span class=\"synConstant\">5<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>     <span class=\"synStatement\">-<\/span><span class=\"synConstant\">3.352<\/span>      <span class=\"synConstant\">1.291<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.597<\/span>   <span class=\"synConstant\">0.0316<\/span> <span class=\"synStatement\">*<\/span>\n<span class=\"synConstant\">50<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>    <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.291<\/span>      <span class=\"synConstant\">1.338<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">1.712<\/span>   <span class=\"synConstant\">0.2234<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>   <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.675<\/span>      <span class=\"synConstant\">1.334<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.005<\/span>   <span class=\"synConstant\">0.1255<\/span>\n<span class=\"synStatement\">---<\/span>\nSignif. codes<span class=\"synSpecial\">:<\/span>  <span class=\"synConstant\">0<\/span> \u2018<span class=\"synError\">***<\/span>\u2019 <span class=\"synConstant\">0.001<\/span> \u2018<span class=\"synStatement\">**<\/span>\u2019 <span class=\"synConstant\">0.01<\/span> \u2018<span class=\"synStatement\">*<\/span>\u2019 <span class=\"synConstant\">0.05<\/span> \u2018.\u2019 <span class=\"synConstant\">0.1<\/span> \u2018 \u2019 <span class=\"synConstant\">1<\/span>\n<span class=\"synSpecial\">(<\/span>Adjusted p values reported <span class=\"synStatement\">--<\/span> single<span class=\"synStatement\">-<\/span>step method<span class=\"synSpecial\">)<\/span>\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30db\u30c3\u30af\u30d0\u30fc\u30b0\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\">\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u3066\u30db\u30c3\u30af\u30d0\u30fc\u30b0\u306e\u65b9\u6cd5\u3067\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\uff1f<\/h2>\n\n\n\n<p>\u30db\u30c3\u30af\u30d0\u30fc\u30b0 Hochberg\u306e\u65b9\u6cd5\u306fBonferroni\u578b\u306ep\u5024\u8abf\u6574\u306e\u3072\u3068\u3064\u3002<\/p>\n\n\n<div class=\"swell-block-postLink\">\t\t\t<div class=\"p-blogCard -internal\" data-type=\"type1\" data-onclick=\"clickLink\">\n\t\t\t\t<div class=\"p-blogCard__inner\">\n\t\t\t\t\t<span class=\"p-blogCard__caption\">\u3042\u308f\u305b\u3066\u8aad\u307f\u305f\u3044<\/span>\n\t\t\t\t\t<div class=\"p-blogCard__thumb c-postThumb\"><figure class=\"c-postThumb__figure\"><img decoding=\"async\" src=\"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2024\/08\/1920x1080-video-Excel-300x169.jpg\" alt=\"\" class=\"c-postThumb__img u-obf-cover\" width=\"320\" height=\"180\"><\/figure><\/div>\t\t\t\t\t<div class=\"p-blogCard__body\">\n\t\t\t\t\t\t<a class=\"p-blogCard__title\" href=\"https:\/\/best-biostatistics.com\/toukei-er\/entry\/multiple-comparison-of-mean-with-bonferroni-type-adjustment-in-r\/\">R \u3067\u30dc\u30f3\u30d5\u30a7\u30ed\u30fc\u30cb\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a>\n\t\t\t\t\t\t<span class=\"p-blogCard__excerpt\">\u691c\u8a3c\u8a66\u9a13\u306b\u304a\u3044\u3066\u3001\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u6bd4\u8f03\u3057\u305f\u3044\u3068\u304d\u306b\u3001\u5358\u7d14\u306b\u4e8c\u7fa4\u6bd4\u8f03\u3092\u7e70\u308a\u8fd4\u3059\u3068\u6709\u610f\u6c34\u6e96\u304c\u7518\u304f\u306a\u308b\u3002 \u6709\u610f\u6c34\u6e96\u306e\u8abf\u6574\u306b\u3088\u3063\u3066\u7c21\u5358\u306b\u51e6\u7406\u3059\u308b\u65b9\u6cd5\u304c\u30dc\u30f3\u30d5\u30a7\u30ed\u30fc\u30cb&#8230;<\/span>\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\n\n\n\n\n\n<p>Tukey\u3068\u540c\u3058\u7dcf\u5f53\u305f\u308a\u30da\u30a2\u3092\u89e3\u6790\u3057\u3066\u3001p\u5024\u8abf\u6574\u6cd5\u3092Hochberg\u306b\u3057\u305f\u3044\u3068\u601d\u3046\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>amod <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nglht.res.t <span class=\"synStatement\">&lt;-<\/span> <span class=\"synIdentifier\">glht<\/span><span class=\"synSpecial\">(<\/span>amod<span class=\"synSpecial\">,<\/span> linfct <span class=\"synStatement\">=<\/span> <span class=\"synIdentifier\">mcp<\/span><span class=\"synSpecial\">(<\/span>dose <span class=\"synStatement\">=<\/span> <span class=\"synConstant\">\"Tukey\"<\/span><span class=\"synSpecial\">))<\/span>\n<span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.t<span class=\"synSpecial\">,<\/span> test <span class=\"synStatement\">=<\/span> <span class=\"synIdentifier\">adjusted<\/span><span class=\"synSpecial\">(<\/span><span class=\"synConstant\">\"hochberg\"<\/span><span class=\"synSpecial\">))<\/span>\n<\/code><\/pre>\n\n\n\n<p>\u3069\u306e\u7fa4\u9593\u3082\u7d71\u8a08\u5b66\u7684\u6709\u610f\u3067\u306f\u306a\u3044\u3002<\/p>\n\n\n\n<p>\u63a7\u3048\u3081\u306a\u7d50\u679c\u3060\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><span class=\"synStatement\">&gt;<\/span> <span class=\"synIdentifier\">summary<\/span><span class=\"synSpecial\">(<\/span>glht.res.t<span class=\"synSpecial\">,<\/span> test <span class=\"synStatement\">=<\/span> <span class=\"synIdentifier\">adjusted<\/span><span class=\"synSpecial\">(<\/span><span class=\"synConstant\">\"hochberg\"<\/span><span class=\"synSpecial\">))<\/span>\nSimultaneous Tests <span class=\"synStatement\">for<\/span> General Linear Hypotheses\nMultiple Comparisons of Means<span class=\"synSpecial\">:<\/span> Tukey Contrasts\nFit<span class=\"synSpecial\">:<\/span> <span class=\"synIdentifier\">aov<\/span><span class=\"synSpecial\">(<\/span>formula <span class=\"synStatement\">=<\/span> weight <span class=\"synStatement\">~<\/span> dose <span class=\"synStatement\">+<\/span> gesttime <span class=\"synStatement\">+<\/span> number<span class=\"synSpecial\">,<\/span> data <span class=\"synStatement\">=<\/span> litter<span class=\"synSpecial\">)<\/span>\nLinear Hypotheses<span class=\"synSpecial\">:<\/span>\nEstimate Std. Error t value <span class=\"synIdentifier\">Pr<\/span><span class=\"synSpecial\">(<\/span><span class=\"synStatement\">&gt;|<\/span>t<span class=\"synStatement\">|<\/span><span class=\"synSpecial\">)<\/span>\n<span class=\"synConstant\">5<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>     <span class=\"synStatement\">-<\/span><span class=\"synConstant\">3.3524<\/span>     <span class=\"synConstant\">1.2908<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.597<\/span>   <span class=\"synConstant\">0.0691<\/span> .\n<span class=\"synConstant\">50<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>    <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.2909<\/span>     <span class=\"synConstant\">1.3384<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">1.712<\/span>   <span class=\"synConstant\">0.3661<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">0<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>   <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.6752<\/span>     <span class=\"synConstant\">1.3343<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">2.005<\/span>   <span class=\"synConstant\">0.2448<\/span>\n<span class=\"synConstant\">50<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">5<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>     <span class=\"synConstant\">1.0615<\/span>     <span class=\"synConstant\">1.3973<\/span>   <span class=\"synConstant\">0.760<\/span>   <span class=\"synConstant\">0.7919<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">5<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>    <span class=\"synConstant\">0.6772<\/span>     <span class=\"synConstant\">1.3394<\/span>   <span class=\"synConstant\">0.506<\/span>   <span class=\"synConstant\">0.7919<\/span>\n<span class=\"synConstant\">500<\/span> <span class=\"synStatement\">-<\/span> <span class=\"synConstant\">50<\/span> <span class=\"synStatement\">==<\/span> <span class=\"synConstant\">0<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.3844<\/span>     <span class=\"synConstant\">1.4510<\/span>  <span class=\"synStatement\">-<\/span><span class=\"synConstant\">0.265<\/span>   <span class=\"synConstant\">0.7919<\/span>\n<span class=\"synStatement\">---<\/span>\nSignif. codes<span class=\"synSpecial\">:<\/span>  <span class=\"synConstant\">0<\/span> \u2018<span class=\"synError\">***<\/span>\u2019 <span class=\"synConstant\">0.001<\/span> \u2018<span class=\"synStatement\">**<\/span>\u2019 <span class=\"synConstant\">0.01<\/span> \u2018<span class=\"synStatement\">*<\/span>\u2019 <span class=\"synConstant\">0.05<\/span> \u2018.\u2019 <span class=\"synConstant\">0.1<\/span> \u2018 \u2019 <span class=\"synConstant\">1<\/span>\n<span class=\"synSpecial\">(<\/span>Adjusted p values reported <span class=\"synStatement\">--<\/span> hochberg method<span class=\"synSpecial\">)<\/span>\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"\u307e\u3068\u3081\">\u307e\u3068\u3081<\/h2>\n\n\n\n<p>\u7d71\u8a08\u30bd\u30d5\u30c8R\u306a\u3089\u3070\u3001\u5171\u5909\u91cf\u3092\u8abf\u6574\u3057\u306a\u304c\u3089\u5e73\u5747\u5024\u306e\u591a\u91cd\u6bd4\u8f03\u304c\u3067\u304d\u308b\u3002<\/p>\n\n\n\n<p>aov()\u3068glht()\u3092\u4f7f\u3063\u3066\u3001Tukey\u3082Dunnett\u3082Hochberg\u3082\u5b9f\u65bd\u3067\u304d\u308b\u3002<\/p>\n\n\n\n<p>\u53c2\u8003\u306b\u306a\u308c\u3070\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u591a\u91cd\u6bd4\u8f03\u3057\u305f\u3044\u3002 \u3067\u3082\u5404\u7fa4\u306e\u80cc\u666f\u56e0\u5b50\u304c\u305d\u308d\u3063\u3066\u3044\u306a\u3044\u3002 \u80cc\u666f\u56e0\u5b50\u3092\u8abf\u6574\u3057\u306a\u304c\u3089\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u591a\u91cd\u6bd4\u8f03\u3059\u308b\u306b\u306f\u3069\u3046\u3059\u308c\u3070\u3044\u3044\u304b\uff1f R \u3067\u306e\u3084\u308a\u65b9\u3092\u89e3\u8aac\u3059\u308b\u3002<\/p>\n","protected":false},"author":2,"featured_media":2806,"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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[5,11,49],"tags":[],"class_list":["post-512","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r","category-11","category-49"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/08\/boxplot_example.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/512","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=512"}],"version-history":[{"count":3,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/512\/revisions"}],"predecessor-version":[{"id":2808,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/512\/revisions\/2808"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/media\/2806"}],"wp:attachment":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/media?parent=512"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/categories?post=512"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/tags?post=512"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}