{"id":484,"date":"2023-07-29T18:24:50","date_gmt":"2023-07-29T18:24:50","guid":{"rendered":"https:\/\/statorials.org\/cn\/r-%e7%9a%84%e5%a4%9a%e5%85%83%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90\/"},"modified":"2023-07-29T18:24:50","modified_gmt":"2023-07-29T18:24:50","slug":"r-%e7%9a%84%e5%a4%9a%e5%85%83%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/r-%e7%9a%84%e5%a4%9a%e5%85%83%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u6267\u884c\u591a\u5143\u65b9\u5dee\u5206\u6790"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u8981\u7406\u89e3\u591a\u5143\u65b9\u5dee\u5206\u6790\uff0c\u9996\u5148\u8981\u7406\u89e3\u65b9\u5dee\u5206\u6790\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u5355\u5411\u65b9\u5dee\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">ANOVA<\/a> \uff08\u65b9\u5dee\u5206\u6790\uff09\u7528\u4e8e\u786e\u5b9a\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u60f3\u77e5\u9053\u5b66\u4e60\u6280\u5de7\u662f\u5426\u5bf9\u67d0\u4e2a\u73ed\u7ea7\u5b66\u751f\u7684\u8003\u8bd5\u6210\u7ee9\u6709\u5f71\u54cd\u3002\u6211\u4eec\u628a\u5168\u73ed\u968f\u673a\u5206\u6210\u4e09\u7ec4\u3002\u6bcf\u4e2a\u5c0f\u7ec4\u5728\u4e00\u4e2a\u6708\u5185\u4f7f\u7528\u4e0d\u540c\u7684\u5b66\u4e60\u6280\u5de7\u6765\u51c6\u5907\u8003\u8bd5\u3002\u6708\u5e95\uff0c\u6240\u6709\u5b66\u751f\u53c2\u52a0\u76f8\u540c\u7684\u8003\u8bd5\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u67e5\u660e\u5b66\u4e60\u6280\u5de7\u662f\u5426\u5bf9\u8003\u8bd5\u6210\u7ee9\u6709\u5f71\u54cd\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790\uff0c\u8fd9\u5c06\u544a\u8bc9\u6211\u4eec\u4e09\u7ec4\u7684\u5e73\u5747\u6210\u7ee9\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u4e0a\u7684\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5728\u65b9\u5dee\u5206\u6790\u4e2d\uff0c\u6211\u4eec\u6709\u4e00\u4e2a\u54cd\u5e94\u53d8\u91cf\u3002\u7136\u800c\uff0c\u5728\u591a\u5143\u65b9\u5dee\u5206\u6790\uff08 <strong>MANOVA<\/strong> \uff09\u4e2d\uff0c\u6211\u4eec\u6709\u591a\u4e2a\u54cd\u5e94\u53d8\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u60f3\u77e5\u9053\u6559\u80b2\u6c34\u5e73\uff08\u5373\u9ad8\u4e2d\u3001\u526f\u5b66\u58eb\u5b66\u4f4d\u3001\u5b66\u58eb\u5b66\u4f4d\u3001\u7855\u58eb\u5b66\u4f4d\u7b49\uff09\u5bf9\u5e74\u6536\u5165\u548c\u5b66\u751f\u503a\u52a1\u91d1\u989d\u7684\u5f71\u54cd\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u6709\u4e00\u4e2a\u56e0\u7d20\uff08\u6559\u80b2\u6c34\u5e73\uff09\u548c\u4e24\u4e2a\u54cd\u5e94\u53d8\u91cf\uff08\u5e74\u6536\u5165\u548c\u5b66\u751f\u503a\u52a1\uff09\uff0c\u56e0\u6b64\u6211\u4eec\u53ef\u4ee5\u6267\u884c\u5355\u5411\u591a\u5143\u65b9\u5dee\u5206\u6790\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong><\/span> <a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u4e86\u89e3\u65b9\u5dee\u5206\u6790\u3001ANCOVA\u3001MANOVA \u548c MANCOVA \u4e4b\u95f4\u7684\u5dee\u5f02<\/a><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u591a\u5143\u65b9\u5dee\u5206\u6790<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5728\u4e0b\u9762\u7684\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c06\u8bf4\u660e\u5982\u4f55\u4f7f\u7528\u5185\u7f6e\u7684<strong>\u9e22\u5c3e\u82b1<\/strong>\u6570\u636e\u96c6\u5728 R \u4e2d\u6267\u884c\u5355\u5411\u591a\u5143\u65b9\u5dee\u5206\u6790\uff0c\u8be5\u6570\u636e\u96c6\u5305\u542b\u6709\u5173\u4e09\u79cd\u4e0d\u540c\u7269\u79cd\uff08\u201csetosa\u201d\u3001\u201cvirginica\u201d\uff09\u7684\u4e0d\u540c\u82b1\u6d4b\u91cf\u7684\u957f\u5ea6\u548c\u5bbd\u5ea6\u7684\u4fe1\u606f\uff0c\u201c\u6742\u8272\u201d\uff09\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#view first six rows of <em>iris<\/em> dataset<\/span>\nhead(iris)\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n#1 5.1 3.5 1.4 0.2 setosa\n#2 4.9 3.0 1.4 0.2 setosa\n#3 4.7 3.2 1.3 0.2 setosa\n#4 4.6 3.1 1.5 0.2 setosa\n#5 5.0 3.6 1.4 0.2 setosa\n#6 5.4 3.9 1.7 0.4 setosa\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u60f3\u77e5\u9053\u7269\u79cd\u662f\u5426\u5bf9\u843c\u7247\u957f\u5ea6\u548c\u5bbd\u5ea6\u6709\u5f71\u54cd\u3002\u4f7f\u7528<em>\u7269\u79cd<\/em>\u4f5c\u4e3a\u81ea\u53d8\u91cf\uff0c\u843c\u7247<em>\u957f\u5ea6<\/em>\u548c<em>\u5bbd\u5ea6<\/em>\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 R \u4e2d\u7684<strong>manova()<\/strong>\u51fd\u6570\u6267\u884c\u5355\u5411\u591a\u5143\u65b9\u5dee\u5206\u6790\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>manova()<\/strong>\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<p style=\"text-align: left;\"><strong><span style=\"color: #000000;\">\u9a6c\u8bfa\u74e6 (cbind (rv1, rv2, \u2026) ~ iv, \u6570\u636e)<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>rv1\u3001rv2<\/strong> \uff1a\u54cd\u5e94\u53d8\u91cf1\u3001\u54cd\u5e94\u53d8\u91cf2\u7b49\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>iv<\/strong> : \u81ea\u53d8\u91cf<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>data<\/strong> : \u6570\u636e\u6846\u7684\u540d\u79f0<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5728\u6211\u4eec\u7684 iris \u6570\u636e\u96c6\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u62df\u5408\u591a\u5143\u65b9\u5dee\u5206\u6790\u5e76\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u663e\u793a\u7ed3\u679c\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit the MANOVA model<\/span>\nmodel &lt;- manova(cbind(Sepal.Length, Sepal.Width) ~ Species, data = iris)\n\n<span style=\"color: #008080;\">#view the results\n<\/span>summary(model)\n# Df Pillai approx F num Df den Df Pr(&gt;F)    \n#Species 2 0.94531 65.878 4,294 &lt; 2.2e-16 ***\n#Residuals 147                                             \n#---\n#Significant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0cF \u7edf\u8ba1\u91cf\u4e3a 65.878\uff0c\u76f8\u5e94\u7684 p \u503c\u975e\u5e38\u5c0f\u3002\u8fd9\u8868\u660e\u6839\u636e\u7269\u79cd\u7684\u4e0d\u540c\uff0c\u843c\u7247\u6d4b\u91cf\u503c\u5b58\u5728\u7edf\u8ba1\u5b66\u4e0a\u7684\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<blockquote>\n<p><span style=\"color: #000000;\"><strong>\u6280\u672f\u8bf4\u660e\uff1a<\/strong>\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0cmanova() \u4f7f\u7528<em>Pillai<\/em>\u68c0\u9a8c\u7edf\u8ba1\u91cf\u3002\u7531\u4e8e\u8be5\u68c0\u9a8c\u7edf\u8ba1\u91cf\u7684\u5206\u5e03\u5f88\u590d\u6742\uff0c\u56e0\u6b64\u8fd8\u63d0\u4f9b\u4e86\u8fd1\u4f3c\u7684 F \u503c\u4ee5\u4fbf\u4e8e\u89e3\u91ca\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b64\u5916\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u6307\u5b9a\u201cRoy\u201d\u3001\u201cHotelling-Lawley\u201d\u6216\u201cWilks\u201d\u4f5c\u4e3a\u8981\u4f7f\u7528\u7684\u68c0\u9a8c\u7edf\u8ba1\u91cf\uff1asummary(model, test = &#8216;Wilks&#8217;)<\/span><\/p>\n<\/blockquote>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u51c6\u786e\u627e\u51fa<em>\u7269\u79cd<\/em>\u5bf9\u843c\u7247<em>\u957f\u5ea6<\/em>\u548c<em>\u5bbd\u5ea6<\/em>\u7684\u5f71\u54cd\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<strong>summary.aov()<\/strong>\u6267\u884c\u5355\u53d8\u91cf\u65b9\u5dee\u5206\u6790\uff0c\u5982\u4ee5\u4e0b\u4ee3\u7801\u6240\u793a\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>summary.aov(model)\n\n\n# Response Sepal.Length:\n# Df Sum Sq Mean Sq F value Pr(&gt;F)    \n#Species 2 63.212 31.606 119.26 &lt; 2.2e-16 ***\n#Residuals 147 38.956 0.265                      \n#---\n#Significant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\n# Response Sepal.Width:\n# Df Sum Sq Mean Sq F value Pr(&gt;F)    \n#Species 2 11.345 5.6725 49.16 &lt; 2.2e-16 ***\n#Residuals 147 16.962 0.1154                      \n#---\n#Significant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4e24\u4e2a\u5355\u53d8\u91cf\u65b9\u5dee\u5206\u6790\u7684 p \u503c\u90fd\u6781\u4f4e\uff08&lt;2.2e-16\uff09\uff0c\u8868\u660e<em>\u7269\u79cd<\/em>\u5bf9<em>\u843c\u7247<\/em><em>\u5bbd\u5ea6<\/em>\u548c\u957f\u5ea6\u5177\u6709\u7edf\u8ba1\u663e\u7740\u5f71\u54cd\u3002<\/span><\/p>\n<h2><strong><span style=\"color: #000000;\">\u53ef\u89c6\u5316\u56e2\u961f\u8d44\u6e90<\/span><\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u5c06\u81ea\u53d8\u91cf<em>\u7269\u79cd<\/em>\u7684\u6bcf\u4e2a\u6c34\u5e73\u7684\u7ec4\u5747\u503c\u53ef\u89c6\u5316\u4e5f\u53ef\u80fd\u5f88\u6709\u7528\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u7406\u89e3\u6211\u4eec\u7684\u7ed3\u679c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<strong>gplots<\/strong>\u5e93\u548c<strong>plotmeans()<\/strong>\u51fd\u6570\u6765\u53ef\u89c6\u5316\u6309<em>\u7269\u79cd<\/em><em>\u5212\u5206\u7684\u843c\u7247\u7684\u5e73\u5747\u957f\u5ea6<\/em>\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load <em>gplots<\/em> library<\/span>\nlibrary(gplots)\n\n<span style=\"color: #008080;\">#visualize mean <em>sepal length<\/em> by <em>species<\/em>\n<\/span>plotmeans(iris$Sepal.Length ~ iris$Species)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u56fe\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff0c\u4e0d\u540c\u7269\u79cd\u7684\u5e73\u5747\u843c\u7247\u957f\u5ea6\u5dee\u5f02\u5f88\u5927\u3002\u8fd9\u4e0e\u6211\u4eec\u7684\u591a\u5143\u65b9\u5dee\u5206\u6790\u7ed3\u679c\u76f8\u5339\u914d\uff0c\u8be5\u7ed3\u679c\u544a\u8bc9\u6211\u4eec\uff0c\u4e0d\u540c\u7269\u79cd\u7684\u843c\u7247\u6d4b\u91cf\u503c\u5b58\u5728\u7edf\u8ba1\u5b66\u4e0a\u7684\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u8fd8\u53ef\u4ee5\u6309<em>\u7269\u79cd<\/em>\u53ef\u89c6\u5316<em>\u843c\u7247\u7684\u5e73\u5747\u5bbd\u5ea6<\/em>\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>plotmeans(iris$Sepal.Width ~ iris$Species)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u53c2\u9605<a href=\"https:\/\/www.rdocumentation.org\/packages\/stats\/versions\/3.5.2\/topics\/manova\" target=\"_blank\" rel=\"noopener\">\u6b64\u5904<\/a><strong>manova()<\/strong>\u51fd\u6570\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u8981\u7406\u89e3\u591a\u5143\u65b9\u5dee\u5206\u6790\uff0c\u9996\u5148\u8981\u7406\u89e3\u65b9\u5dee\u5206\u6790\u3002 ANOVA \uff08\u65b9\u5dee\u5206\u6790\uff09\u7528\u4e8e\u786e\u5b9a\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728 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