{"id":1542,"date":"2023-07-25T23:14:40","date_gmt":"2023-07-25T23:14:40","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%a5%a5%e7%89%b9%e6%9b%bc%e5%89%a7%e6%83%85r\/"},"modified":"2023-07-25T23:14:40","modified_gmt":"2023-07-25T23:14:40","slug":"%e5%a5%a5%e7%89%b9%e6%9b%bc%e5%89%a7%e6%83%85r","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%a5%a5%e7%89%b9%e6%9b%bc%e5%89%a7%e6%83%85r\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u521b\u5efa bland-altman \u56fe\uff08\u9010\u6b65\uff09"},"content":{"rendered":"

<\/p>\n

\n

Bland-Altman \u56fe<\/a>\u7528\u4e8e\u53ef\u89c6\u5316\u4e24\u79cd\u4e0d\u540c\u4eea\u5668\u6216\u4e24\u79cd\u4e0d\u540c\u6d4b\u91cf\u6280\u672f\u4e4b\u95f4\u7684\u6d4b\u91cf\u5dee\u5f02\u3002<\/span><\/p>\n

\u5b83\u5bf9\u4e8e\u786e\u5b9a\u4e24\u79cd\u4eea\u5668\u6216\u6280\u672f\u5728\u6d4b\u91cf\u540c\u4e00\u6982\u5ff5\u65f6\u7684\u76f8\u4f3c\u7a0b\u5ea6\u5f88\u6709\u7528\u3002<\/span><\/p>\n

\u672c\u6559\u7a0b\u63d0\u4f9b\u4e86\u5982\u4f55\u5728 R \u4e2d\u521b\u5efa Bland-Altman \u56fe\u7684\u5206\u6b65\u793a\u4f8b\u3002<\/span><\/p>\n

\u7b2c 1 \u6b65\uff1a\u521b\u5efa\u6570\u636e<\/strong><\/span><\/h3>\n

\u5047\u8bbe\u751f\u7269\u5b66\u5bb6\u4f7f\u7528\u4e24\u79cd\u4e0d\u540c\u7684\u4eea\u5668\uff08A \u548c B\uff09\u6d4b\u91cf\u540c\u4e00\u7ec4 20 \u53ea\u4e0d\u540c\u9752\u86d9\u7684\u91cd\u91cf\uff08\u4ee5\u514b\u4e3a\u5355\u4f4d\uff09\u3002<\/span><\/p>\n

\u6211\u4eec\u5c06\u5728 R \u4e2d\u521b\u5efa\u4ee5\u4e0b\u6570\u636e\u6846\uff0c\u8868\u793a\u6bcf\u53f0\u4eea\u5668\u6d4b\u91cf\u7684\u6bcf\u53ea\u9752\u86d9\u7684\u91cd\u91cf\uff1a<\/span><\/p>\n

 #create data<\/span>\ndf <- data. frame<\/span> (A=c(5, 5, 5, 6, 6, 7, 7, 7, 8, 8, 9,\n                     10, 11, 13, 14, 14, 15, 18, 22, 25),\n                 B=c(4, 4, 5, 5, 5, 7, 8, 6, 9, 7, 7, 11,\n                     13, 13, 12, 13, 14, 19, 19, 24))\n\n#view first six rows of data\n<\/span>head(df)\n\n  AB\n1 5 4\n2 5 4\n3 5 5\n4 6 5\n5 6 5\n6 7 7<\/strong><\/pre>\n
\u7b2c 2 \u6b65\uff1a\u8ba1\u7b97\u6d4b\u91cf\u503c\u7684\u5dee\u5f02<\/strong><\/span><\/h3>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u5728\u6570\u636e\u6846\u4e2d\u521b\u5efa\u4e24\u4e2a\u65b0\u5217\uff0c\u5176\u4e2d\u5305\u542b\u6bcf\u53ea\u9752\u86d9\u7684\u5e73\u5747\u6d4b\u91cf\u503c\u4ee5\u53ca\u6d4b\u91cf\u503c\u7684\u5dee\u5f02\uff1a<\/span><\/p>\n
 #create new column for average measurement<\/span>\ndf$avg <- rowMeans(df) \n<\/span>\n#create new column for difference in measurements\ndf$diff <- df$A - df$B<\/span><\/span>\n\n#view first six rows of data\n<\/span>head(df)\n\n  AB avg diff\n1 5 4 4.5 1\n2 5 4 4.5 1\n3 5 5 5.0 0\n4 6 5 5.5 1\n5 6 5 5.5 1\n6 7 7 7.0 0\n<\/strong><\/pre>\n
\u6b65\u9aa4 3\uff1a\u8ba1\u7b97\u5747\u503c\u5dee\u548c\u7f6e\u4fe1\u533a\u95f4<\/strong><\/span><\/h3>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8ba1\u7b97\u4e24\u53f0\u4eea\u5668\u6d4b\u91cf\u503c\u7684\u5e73\u5747\u5dee\u5f02\u4ee5\u53ca\u5e73\u5747\u5dee\u5f02\u7684 95% \u7f6e\u4fe1\u533a\u95f4\u7684\u4e0a\u9650\u548c\u4e0b\u9650\uff1a<\/span><\/p>\n
 #find average difference<\/span>\nmean_diff <- mean(df$diff)\n\nmean_diff\n\n[1] 0.5\n<\/span>\n#find lower 95% confidence interval limits\nlower <- mean_diff - 1.96*sd(df$diff)<\/span>\n\nlower\n\n[1] -1.921465\n<\/span>\n#find upper 95% confidence interval limits\nupper <- mean_diff + 1.96*sd(df$diff)<\/span>\n\nupper<\/span>\n\n[1] 2.921465\n<\/span><\/span><\/strong><\/pre>\n
\u5e73\u5747\u5dee\u503c\u4e3a0.5<\/strong> \uff0c\u5e73\u5747\u5dee\u503c\u7684 95% \u7f6e\u4fe1\u533a\u95f4\u4e3a[-1.921, 2.921]<\/strong> \u3002<\/span><\/p>\n
\u7b2c 4 \u6b65\uff1a\u521b\u5efa Bland-Altman \u56fe<\/strong><\/span><\/h3>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u4f7f\u7528ggplot2<\/a>\u6570\u636e\u53ef\u89c6\u5316\u5305\u521b\u5efa Bland-Altman \u56fe\uff1a<\/span><\/span> <\/p>\n
 #load ggplot2\n<\/span><\/span>library<\/span> (ggplot2)\n\n#create Bland-Altman plot\n<\/span>ggplot(df, aes<\/span> (x = avg, y = diff)) +\n  geom_point(size=2) +\n  geom_hline(yintercept = mean_diff) +\n  geom_hline(yintercept = lower, color = \" red<\/span> \", linetype=\" dashed<\/span> \") +\n  geom_hline(yintercept = upper, color = \" red<\/span> \", linetype=\" dashed<\/span> \") +\n  ggtitle(\" Bland-Altman Plot<\/span> \") +\n  ylab(\" Difference Between Measurements<\/span> \") +\n  xlab(\" Average Measurement<\/span> \")<\/span><\/strong> <\/pre>\n
\"R<\/p>\n
\u7ed8\u56fe\u7684 x \u8f74\u663e\u793a\u4e24\u53f0\u4eea\u5668\u7684\u5e73\u5747\u6d4b\u91cf\u503c\uff0cy \u8f74\u663e\u793a\u4e24\u53f0\u4eea\u5668\u4e4b\u95f4\u7684\u6d4b\u91cf\u503c\u5dee\u5f02\u3002<\/span><\/p>\n
\u9ed1\u7ebf\u4ee3\u8868\u4e24\u53f0\u4eea\u5668\u4e4b\u95f4\u6d4b\u91cf\u503c\u7684\u5e73\u5747\u5dee\u5f02\uff0c\u800c\u4e24\u6761\u7ea2\u8272\u865a\u7ebf\u4ee3\u8868\u5e73\u5747\u5dee\u5f02\u7684 95% \u7f6e\u4fe1\u533a\u95f4\u7684\u9650\u503c\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
Bland-Altman \u56fe\u7528\u4e8e\u53ef\u89c6\u5316\u4e24\u79cd\u4e0d\u540c\u4eea\u5668\u6216\u4e24\u79cd\u4e0d\u540c\u6d4b\u91cf\u6280\u672f\u4e4b\u95f4\u7684\u6d4b\u91cf\u5dee\u5f02\u3002 \u5b83\u5bf9\u4e8e\u786e\u5b9a\u4e24\u79cd\u4eea\u5668\u6216\u6280\u672f […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-1542","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 R \u4e2d\u521b\u5efa Bland-Altman \u56fe\uff08\u9010\u6b65\uff09<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 R \u4e2d\u521b\u5efa Bland-Altman \u56fe\uff0c\u5305\u62ec\u5206\u6b65\u793a\u4f8b\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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