{"id":1396,"date":"2023-07-06T08:33:23","date_gmt":"2023-07-05T23:33:23","guid":{"rendered":"https:\/\/info.zanet.biz\/?p=1396"},"modified":"2023-07-18T15:39:34","modified_gmt":"2023-07-18T06:39:34","slug":"bias-dag-directed-acyclic-graph%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"https:\/\/info.zanet.biz\/?p=1396","title":{"rendered":"Bias – DAG Directed Acyclic Graph\u3092\u7528\u3044\u308b\u5206\u6790"},"content":{"rendered":"\n

\u30d0\u30a4\u30a2\u30b9\u3068\u306f<\/strong><\/p>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306f\u300c\u7814\u7a76\u7d50\u679c\u306e\u7cfb\u7d71\u7684\u306a\u504f\u308a\u3001\u3042\u308b\u3044\u306f\u3001\u63a8\u5b9a\u306e\u771f\u5b9f\u304b\u3089\u306e\u7cfb\u7d71\u7684\u306a\u504f\u308a\u300d\u3068\u5b9a\u7fa9\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u7cfb\u7d71\u7684\u3068\u306f\uff1f \u5076\u7136\u306b\u3088\u308b\u504f\u308a\u306b\u5bfe\u3057\u3066\u3001\u5076\u7136\u8d77\u304d\u308b\u504f\u308a\u3067\u306f\u306a\u3044\u306e\u3067\u3001\u7cfb\u7d71\u7684\u306a\u504f\u308a\u3068\u8a00\u3044\u307e\u3059\u3002\u7cfb\u7d71\u7684systematic vs \u5076\u7136random \u3068\u3044\u3046\u8003\u3048\u65b9\u3092\u3057\u3066\u3044\u308b\u3068\u3044\u3046\u3053\u3068\u3067\u3059\u3002\u5076\u7136\u306b\u3088\u308b\u504f\u308a\u306f\u3001\u7d71\u8a08\u5b66\u7684\u306b\u8aac\u660e\u53ef\u80fd\u3067\u30b5\u30f3\u30d7\u30eb\u30b5\u30a4\u30ba\u304c\u5c0f\u3055\u3044\u307b\u3069\u5927\u304d\u304f\u306a\u308a\u307e\u3059\u3002\u30d0\u30a4\u30a2\u30b9\u306b\u3088\u308b\u504f\u308a\u306f\u7d4c\u9a13\u7684empirical\u306a\u30c7\u30fc\u30bf\u306f\u9650\u3089\u308c\u3066\u304a\u308a\u3001\u30d0\u30a4\u30a2\u30b9\u52b9\u679c\u306e\u5927\u304d\u3055\u3068\u65b9\u5411\uff08\u904e\u5927\u8a55\u4fa1\u304b\u904e\u5c0f\u8a55\u4fa1\u304b\uff09\u306b\u3064\u3044\u3066\u306f\u8a55\u4fa1\u8005\u304c\u63a8\u5b9a\u305b\u3056\u308b\u3092\u3048\u306a\u3044\u3053\u3068\u304c\u307b\u3068\u3093\u3069\u3067\u3059\u3002<\/p>\n\n\n\n

\u5b9f\u969b\u306b\u5f97\u3089\u308c\u305f\u7d50\u679c\u306e\u52b9\u679c\u63a8\u5b9a\u5024\u304a\u3088\u3073\u4fe1\u983c\u533a\u9593Confidence interval\u304b\u3089\u3001\u5076\u7136\u306b\u3088\u308b\u504f\u308a\u3060\u3051\u306a\u306e\u304b\u3001\u30d0\u30a4\u30a2\u30b9\u306b\u3088\u308b\u504f\u308a\u306a\u306e\u304b\u3001\u4e21\u65b9\u304c\u6df7\u3056\u3063\u3066\u3044\u308b\u306e\u304b\u3092\u898b\u5206\u3051\u308b\u306e\u306f\u96e3\u3057\u3044\u3067\u3059\u3002\u306a\u304a\u3001\u983b\u5ea6\u8ad6\u6d3eFrequentist\u306e95%\u4fe1\u983c\u533a\u9593\u306f\u540c\u3058\u3053\u3068\u3092\u7e70\u308a\u8fd4\u3057\u305f\u308995%\u306e\u5834\u5408\u306f\u305d\u306e\u7bc4\u56f2\u306b\u672c\u5f53\u306e\u5024\u304c\u542b\u307e\u308c\u308b\u3068\u3044\u3046\u3053\u3068\u3092\u610f\u5473\u3057\u3066\u3044\u307e\u3059\u30025\uff05\u306e\u5834\u5408\u306f\u3001\u305d\u306e\u7bc4\u56f2\u5916\u306b\u306a\u308a\u307e\u3059\u3002\u30d9\u30a4\u30b8\u30a2\u30f3Bayesian\u306e\u30a2\u30d7\u30ed\u30fc\u30c1\u3067\u3042\u308c\u3070\u300195%\u78ba\u4fe1\u533a\u9593Credicble interval\u306f\u771f\u306e\u5024\u309295%\u306e\u78ba\u7387\u3067\u542b\u3080\u7bc4\u56f2\u3067\u3059\u3002<\/p>\n\n\n\n

\u3055\u3066\u3001\u30d0\u30a4\u30a2\u30b9\u306f\u591a\u6570\u5b58\u5728\u3057\u307e\u3059\u304c\u3001\u30d0\u30a4\u30a2\u30b9\u306e\u539f\u56e0\u3068\u306a\u308b\u8981\u7d20\u304c\u305d\u306e\u7814\u7a76\u306b\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u3053\u3068\u306f\u53ef\u80fd\u3067\u3059\u3002\u305d\u308c\u304c\u305d\u306e\u7814\u7a76\u306b\u3042\u308c\u3070\u3001\u305d\u306e\u7d50\u679c\u3042\u308b\u3044\u306f\u52b9\u679c\u63a8\u5b9a\u5024\u306f\u30d0\u30a4\u30a2\u30b9\u306e\u305f\u3081\u3001\u504f\u3063\u3066\u3044\u308b\u53ef\u80fd\u6027\u304c\u9ad8\u304f\u306a\u308a\u307e\u3059\u3002\u305d\u306e\u3088\u3046\u306a\u30a2\u30d7\u30ed\u30fc\u30c1\u304c\u5fc5\u8981\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u771f\u306e\u5024\u3092\u63a8\u5b9a\u3059\u308b\u3053\u3068\u306f\u3001\u3082\u3057\u30d0\u30a4\u30a2\u30b9\u52b9\u679c\u306e\u5927\u304d\u3055\u304c\u63a8\u5b9a\u3067\u304d\u308c\u3070\u3001\u305d\u308c\u306b\u3088\u3063\u3066\u8abf\u6574\u3059\u308b\u3053\u3068\u3067\u3001\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\uff08Quantitative bias analysis\uff09\u3002\u4f8b\u3048\u3070\u3001\u5f97\u3089\u308c\u305f\u7d50\u679c\u306e\u30ea\u30b9\u30af\u6bd4RR\uff1d0.8\u3067\u3001\u30d0\u30a4\u30a2\u30b9\u306e\u52b9\u679c\u304cRR\uff1d0.9\u3067\u3042\u308c\u3070\u3001\u771f\u306e\u52b9\u679c\u63a8\u5b9a\u5024\u306fRR \uff1d 0.8\/0.9 = 0.89 =exp[ln(0.8)-ln(0.9)] = exp[-0.223-(-0.105)] = exp(-0.118)\u3067\u3059\u3002\u7d50\u679cRR\u306e\u5206\u6563\u3068\u30d0\u30a4\u30a2\u30b9\u52b9\u679c\u306eRR\u306e\u5206\u6563\u3092\u5408\u8a08\u3059\u308b\u3068\u30d0\u30a4\u30a2\u30b9\u3067\u8abf\u6574\u3057\u305f\u771f\u306e\u52b9\u679c\u306e\u63a8\u5b9a\u5024\u306e\u5206\u6563\u306f\u305d\u308c\u3089\u306e\u5408\u8a08\u306b\u306a\u308a\u307e\u3059\u3002\u30d0\u30a4\u30a2\u30b9\u52b9\u679c\u306eRR\u306e\u5206\u6563\u306f\u30ec\u30d3\u30e5\u30a2\u304c\u63a8\u5b9a\u5024\u3092\u8a2d\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\uff08Turner RM 2009\uff09\u3002\uff0aln \u81ea\u7136\u5bfe\u6570\uff1bexp Exponential \uff08Excel\u306e\u95a2\u6570\u306e\u8868\u793aln(), exp()\u3068\u540c\u3058\u3067\u3059, \u306a\u304a\u3001R\u3067\u306f\u81ea\u7136\u5bfe\u6570\u306flog()\uff09\u3002<\/p>\n\n\n\n

\u307e\u305f\u3001\u30d0\u30a4\u30a2\u30b9\u306e\u52b9\u679c\u306e\u5927\u304d\u3055\u304c\u3069\u308c\u4f4d\u3042\u308c\u3070\u671b\u307e\u3057\u3044\u7d50\u679c\u304c\u671b\u307e\u3057\u304f\u306a\u3044\u7d50\u679c\u306b\u53cd\u8ee2\u3059\u308b\u304b\u3082\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\uff08Bias adjustment thresholds analysis\uff09\uff08Phillippo DM 2018\uff09\u3002\u3057\u304b\u3057\u306a\u304c\u3089\u3001\u305d\u3053\u307e\u3067\u5206\u6790\u3092\u884c\u3046\u30b1\u30fc\u30b9\u306f\u5c11\u306a\u304f\u3001Cochrane risk of bias tool\u306e\u3088\u3046\u306b\u3001\u5927\u304d\u306a\u30d0\u30a4\u30a2\u30b9\uff08\u3042\u308b\u3044\u306f\u201d\u5b9f\u8cea\u7684\u306a\u30d0\u30a4\u30a2\u30b9\u201d material bias\uff09\u306e\u30ea\u30b9\u30af\uff1d\u53ef\u80fd\u6027\u304c\u3069\u308c\u304f\u3089\u3044\u3042\u308b\u304b\u3092\u8a55\u4fa1\u3059\u308b\u3053\u3068\u304c\u4e00\u822c\u7684\u3067\u3059\u3002<\/p>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306f\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9\u3001\u9078\u629e\u30d0\u30a4\u30a2\u30b9\u3001\u60c5\u5831\u30d0\u30a4\u30a2\u30b9\u306e\uff13\u3064\u306b\u5206\u985e\u3055\u308c\u308b\u306e\u304c\u4e00\u822c\u7684\u3067\u3059\uff08Lash TL 2021\uff09\u3002<\/p>\n\n\n\n

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\u56f3 \u30d0\u30a4\u30a2\u30b9\u306e\uff13\u3064\u306e\u30bf\u30a4\u30d7\u3068DAG\u3002
\u77e2\u5370\u306e\u59cb\u70b9\u306e\u65b9\u304c\u539f\u56e0\u3067\u7d42\u70b9\u306e\u65b9\u304c\u7d50\u679c\u3092\u793a\u3057\u307e\u3059\u3002I\u306fIntervention\u4ecb\u5165\u307e\u305f\u306fE\u3068\u66f8\u3044\u3066Exposure\u8981\u56e0\u66b4\u9732\u3001C\u306fCommon cause\u5171\u901a\u539f\u56e0\uff1dConfounder\u4ea4\u7d61\u56e0\u5b50\u3001O\u306fOutcome\u30a2\u30a6\u30c8\u30ab\u30e0\u3092\u8868\u3057\u307e\u3059\u3002Oi<\/sub>\u306fIntermediate outcome\u4e2d\u9593\u30a2\u30a6\u30c8\u30ab\u30e0\u3001Oe<\/sub>\u306fEndpoint\u30a8\u30f3\u30c9\u30dd\u30a4\u30f3\u30c8\u3067\u3059\u3002I*\u306f\u6e2c\u5b9a\u3055\u308c\u305f\u4ecb\u5165\u3001O*\u306f\u6e2c\u5b9a\u3055\u308c\u305f\u30a2\u30a6\u30c8\u30ab\u30e0\u3092\u8868\u3057\u307e\u3059\u3002U\u306f\u6e2c\u5b9a\u8aa4\u5dee\u3092\u5f15\u304d\u8d77\u3053\u3059\u56e0\u5b50\u3067\u3001\u591a\u304f\u306e\u5834\u5408\u4e0d\u660e\u3067\u3059\u3002
\u5171\u901a\u539f\u56e0\u306f\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9\u3001\u5171\u901a\u52b9\u679c\u306f\u9078\u629e\u30d0\u30a4\u30a2\u30b9\u3001\u7cfb\u7d71\u7684\u6e2c\u5b9a\u8aa4\u5dee\u306f\u60c5\u5831\u30d0\u30a4\u30a2\u30b9\u306b\u5bfe\u5fdc\u3057\u307e\u3059\u3002
I\u2190C\u2192O; I\u2192S\u2192Oi<\/sub>\u2190Oe<\/sub>\u3068\u8a18\u8ff0\u3057\u3066\u3082\u5171\u901a\u539f\u56e0\u3001\u5171\u901a\u52b9\u679c\u3067\u3042\u308b\u3053\u3092\u3068\u8868\u73fe\u3067\u304d\u307e\u3059\u3002<\/figcaption><\/figure>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306e\u52b9\u679c\u3092\u5206\u6790\u3059\u308b\u969b\u306b\u3001\u6709\u5411\u975e\u5de1\u56de\u30b0\u30e9\u30d5Directed Acyclic Graph (DAG)<\/strong>\u304c\u7528\u3044\u3089\u308c\u308b\u3053\u3068\u304c\u3042\u308a\u307e\u3059\u3002DAG\u306f\u56e0\u679c\u95a2\u4fc2\u56f3Causal Diagram<\/strong>\u3068\u547c\u3070\u308c\u308b\u3053\u3068\u3082\u3042\u308a\u307e\u3059\u3002\u305d\u308c\u305e\u308c\u306e\u5909\u6570\u304c\u30d0\u30a4\u30a2\u30b9\u306b\u306a\u308a\u3046\u308b\u304b\u3092\u691c\u8a0e\u3059\u308b\u306e\u306b\u6709\u529b\u306a\u30c4\u30fc\u30eb\u3067\u3059\u3002\u56f3\u306b\u306f\u3001Luijendijk HJ 2020\u306e\u8ad6\u6587\u306b\u57fa\u3065\u3044\u3066\u3001\u6c4e\u7528\u6027\u306e\u3042\u308bDAG\u306e\uff13\u3064\u306e\u30d0\u30a4\u30a2\u30b9\u306e\u30bf\u30a4\u30d7\u306b\u3064\u3044\u3066\u793a\u3057\u3066\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u5171\u901a\u52b9\u679c<\/strong>\u2192\u9078\u629e\u30d0\u30a4\u30a2\u30b9<\/p>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306e\u8b70\u8ad6\u306e\u969b\u306b\u3001\u3088\u304f\u5f15\u7528\u3055\u308c\u308bBerkson’s bias\u306f\u9078\u629e\u30d0\u30a4\u30a2\u30b9\u3068\u3057\u3066\u77e5\u3089\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u5171\u901a\u52b9\u679c\u306eDAG\u3092\u4f7f\u3063\u3066\u8aac\u660e\u3055\u308c\u307e\u3059(Westreich D 2012)\u3002\u4f8b\u3048\u3070\u3001\u30af\u30ea\u30cb\u30c3\u30af\u53d7\u8a3a\u60a3\u8005\u3092\u5bfe\u8c61\u3068\u3057\u3066\u7cd6\u5c3f\u75c5\u3068\u8a8d\u77e5\u75c7\u306e\u95a2\u4fc2\u3092\u5206\u6790\u3057\u305f\u5834\u5408\u3001\u53d7\u8a3a\u306e\u539f\u56e0\u304c\u7cd6\u5c3f\u75c5\u306e\u5834\u5408\u3082\u3042\u308a\u8a8d\u77e5\u75c7\u306e\u5834\u5408\u3082\u3042\u308a\u307e\u3059\u3002\u30af\u30ea\u30cb\u30c3\u30af\u53d7\u8a3a\u304c\u5171\u901a\u52b9\u679c\u306b\u306a\u308a\u307e\u3059\u3002\u30af\u30ea\u30cb\u30c3\u30af\u3092\u53d7\u8a3a\u3057\u306a\u3044\u60a3\u8005\u306f\u9078\u629e\u305b\u305a\u3001\u30af\u30ea\u30cb\u30c3\u30af\u53d7\u8a3a\u60a3\u8005\u3060\u3051\u3092\u9078\u629e\u3057\u3066\u7cd6\u5c3f\u75c5\u3068\u8a8d\u77e5\u75c7\u306e\u95a2\u4fc2\u3092\u5206\u6790\u3059\u308b\u3068\u30d0\u30a4\u30a2\u30b9\u304c\u751f\u3058\u307e\u3059\u3002\u3053\u306e\u3088\u3046\u306a\u30d0\u30a4\u30a2\u30b9\u306f\u3001\u524d\u5411\u304d\u7814\u7a76\u3067\u3082\u5f8c\u308d\u5411\u304d\u7814\u7a76\u3067\u3082\u3001\u89b3\u5bdf\u7814\u7a76\u3067\u3082\u30e9\u30f3\u30c0\u30e0\u5316\u6bd4\u8f03\u8a66\u9a13\u3067\u3082\u8d77\u304d\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u5171\u901a\u52b9\u679c\u3067\u6761\u4ef6\u4ed8\u3051\u3055\u308c\u308b\u3059\u306a\u308f\u3061conditioned on \uff08\u5206\u985e\u3055\u308c\u308b\uff09\u3042\u308b\u5c64\u3060\u3051\u3092\u5bfe\u8c61\u3068\u3057\u3066\u9078\u629e\u3057\u305f\u308a\u3001\u5171\u901a\u52b9\u679c\u3067\u8abf\u6574\u3059\u308b\u3068\u30d0\u30a4\u30a2\u30b9\u304c\u751f\u3058\u307e\u3059\u3002\u3059\u306a\u308f\u3061\u3001\u56f3\u306b\u793a\u3059\u5909\u6570S\u306b\u57fa\u3065\u304f\u5c64\u306e\u3072\u3068\u3064\u3092\u5206\u6790\u3059\u308b\u3001\u3042\u308b\u3044\u306f\u5909\u6570S\u3067I\u3068Oe<\/sub>\u306e\u95a2\u4fc2\u3092\u8abf\u6574\u3057\u305f\u5206\u6790\u3092\u884c\u3046\u3068\u30d0\u30a4\u30a2\u30b9\u304c\u751f\u3058\u307e\u3059\u3002\u3053\u306e\u3088\u3046\u306a\u30d0\u30a4\u30a2\u30b9\u306e\u7d50\u679c\u306f\u904e\u5927\u8a55\u4fa1\u306b\u306a\u308b\u5834\u5408\u3082\u3001\u904e\u5c0f\u8a55\u4fa1\u306b\u306a\u308b\u5834\u5408\u3082\u3042\u308a\u3001\u4f8b\u3048\u3070\u3001\u4e0a\u8a18\u306e\u4f8b\u3060\u3068\u7cd6\u5c3f\u75c5\u306f\u8a8d\u77e5\u75c7\u306e\u30ea\u30b9\u30af\u3092\u9ad8\u3081\u308b\u3053\u3068\u306f\u306a\u3044\u3068\u3044\u3046\u7d50\u679c\u304c\u5f97\u3089\u308c\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

S\u304cOi<\/sub>\u306e\u5f71\u97ff\u3092\u3046\u3051\u3066\u5909\u52d5\u3059\u308b\u7d50\u679c\u751f\u3058\u308b\u30d0\u30a4\u30a2\u30b9\u3068\u3057\u3066\u3001\u8131\u843d\u306b\u3088\u308b\u30d0\u30a4\u30a2\u30b9\u3001\u75c7\u4f8b\u6e1b\u5c11\u30d0\u30a4\u30a2\u30b9Attrition bias\u304c\u3042\u308a\u307e\u3059\u3002\u305d\u306e\u5834\u5408\u3001\u4ecb\u5165\u7fa4\u306e\u65b9\u3067\u8131\u843d\u304c\u3088\u308a\u591a\u3044\u3068\u3044\u3046\u3088\u3046\u306a\u3001I\u304b\u3089\u306e\u5f71\u97ff\u3082\u53d7\u3051\u307e\u3059\u3002<\/p>\n\n\n\n

\u30b3\u30f3\u30b7\u30fc\u30eb\u30e1\u30f3\u30c8\u304c\u306a\u3044\u305f\u3081\u306b\u30e9\u30f3\u30c0\u30e0\u5316\u304c\u6b6a\u3093\u3067\u8d77\u304d\u308b\u30d0\u30a4\u30a2\u30b9\u3082\u5171\u901a\u52b9\u679c\u3067\u8aac\u660e\u3067\u304d\u308b\u306f\u305a\u3067\u3059\u3002\u7686\u3055\u3093\u3082\u8003\u3048\u3066\u307f\u3066\u4e0b\u3055\u3044\u3002<\/p>\n\n\n\n

\u5171\u901a\u52b9\u679c\u306fCollider \u5408\u6d41\u56e0\u5b50\u3068\u3082\u547c\u3070\u308c\u3001\u5171\u901a\u52b9\u679c\u306b\u3088\u308b\u30d0\u30a4\u30a2\u30b9\u306f\u9078\u629e\u30d0\u30a4\u30a2\u30b9\u306b\u76f8\u5f53\u3057\u307e\u3059\u3002\u9078\u629e\u30d0\u30a4\u30a2\u30b9\u3092Collider bias\u3068\u547c\u3076\u3053\u3068\u3082\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u5171\u901a\u539f\u56e0<\/strong>\u2192\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9<\/p>\n\n\n\n

\u5171\u901a\u539f\u56e0\u306f\u4ea4\u7d61\u56e0\u5b50\u306b\u76f8\u5f53\u3057\u3001\u4ecb\u5165\u3068\u30a2\u30a6\u30c8\u30ab\u30e0\u306e\u4e21\u65b9\u306b\u95a2\u4fc2\u304c\u3042\u308b\u56e0\u5b50\u3067\u3059\u3002\u56e0\u679c\u95a2\u4fc2\u306fI\u2190C\u2192O\u306e\u65b9\u5411\u3067\u3059\u3002\u5171\u901a\u539f\u56e0\uff1d\u4ea4\u7d61\u56e0\u5b50\u306e\u5f71\u97ff\u306b\u3088\u3063\u3066\u4ecb\u5165\u304c\u5909\u52d5\u3057\u3001\u30a2\u30a6\u30c8\u30ab\u30e0\u3082\u5909\u52d5\u3059\u308b\u5834\u5408\u306b\u3001\u4ecb\u5165\u306e\u30a2\u30a6\u30c8\u30ab\u30e0\u306b\u5bfe\u3059\u308b\u52b9\u679c\u3092\u5358\u7d14\u306b\u5206\u6790\u3059\u308b\u3068\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9\u304c\u751f\u3058\u307e\u3059\u3002\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9\u306f\u5206\u6790\u306e\u6642\u70b9\u3067\u5c64\u5225\u5206\u6790\u3084\u591a\u5909\u91cf\u56de\u5e30\u5206\u6790\u306a\u3069\u3067\u8abf\u6574\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\u304c\u8abf\u6574\u306e\u7a0b\u5ea6\u306f\u3055\u307e\u3056\u307e\u3067\u3059\u3002<\/p>\n\n\n\n

\u4f8b\u3048\u3070\u3001\u76f2\u691c\u5316\u304c\u3055\u308c\u3066\u3044\u306a\u3044\u305f\u3081\u201c\u5225\u306e\u6cbb\u7642\u3092\u53d7\u3051\u308b\u201d\u3068\u3044\u3046\u201c\u6cbb\u7642\u4f01\u56f3\u304b\u3089\u306e\u4e56\u96e2\u201d\u304c\u8d77\u304d\u308b\u3068\u3001\u5bfe\u8c61\u8005\u306e\u4ecb\u5165\u306e\u5185\u5bb9\u3092\u5909\u3048\u3001\u6cbb\u7642\u306e\u52b9\u679c\uff1d\u30a2\u30a6\u30c8\u30ab\u30e0\u3092\u5909\u3048\u3066\u3057\u307e\u3046\u306e\u3067\u3001\u4ea4\u7d61\u56e0\u5b50\u306b\u306a\u308a\u307e\u3059\u3002\u5171\u901a\u539f\u56e0\u306b\u3088\u308a\u751f\u3058\u308b\u30d0\u30a4\u30a2\u30b9\u306f\u4ea4\u7d61\u30d0\u30a4\u30a2\u30b9\u306b\u76f8\u5f53\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u7cfb\u7d71\u7684\u6e2c\u5b9a\u8aa4\u5dee<\/strong>\u2192\u60c5\u5831\u30d0\u30a4\u30a2\u30b9<\/p>\n\n\n\n

\u7cfb\u7d71\u7684\u6e2c\u5b9a\u8aa4\u5dee\u3042\u308b\u3044\u306f\u8aa4\u5206\u985e\u306f\u3055\u307e\u3056\u307e\u306a\u539f\u56e0\u3067\u8d77\u304d\u307e\u3059\u3002\u56f3\u306b\u793a\u3059U\u306f\u3001\u672a\u77e5\u306e\u56e0\u5b50\u3067\u3059\u304c\u3001\u305d\u308c\u304c\u5f71\u97ff\u3057\u3066\u6e2c\u5b9a\u8aa4\u5dee\u304c\u751f\u3058\u305f\u4ecb\u5165\u304cI*\u3001\u30a2\u30a6\u30c8\u30ab\u30e0\u304cO*\u3067\u3059\u3002\u6e2c\u5b9a\u8aa4\u5dee\u306e\u539f\u56e0\u304cI\u306b\u3042\u308b\u5834\u5408\u3082\uff08\u8d64\u3044\u77e2\u5370\uff09\u3001O\u306b\u3042\u308b\u5834\u5408\u3082\uff08\u7dd1\u306e\u77e2\u5370\uff09\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u4f8b\u3048\u3070\u3001\u76f2\u691c\u5316\u304c\u3055\u308c\u3066\u3044\u306a\u3044\u305f\u3081\u306b\u3001\u30a2\u30a6\u30c8\u30ab\u30e0\u6e2c\u5b9a\u8005\u304c\u60a3\u8005\u304c\u53d7\u3051\u3066\u3044\u308b\u6cbb\u7642\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u305f\u3081\u3001\u4ecb\u5165\u306b\u6709\u5229\u306a\u6e2c\u5b9a\u7d50\u679c\u3092\u51fa\u3057\u3066\u3057\u307e\u3044\u3001\u904e\u5927\u8a55\u4fa1\u306e\u7d50\u679c\u304c\u5f97\u3089\u308c\u305f\u5834\u5408\u3001\u7cfb\u7d71\u7684\u6e2c\u5b9a\u8aa4\u5dee\u306e\u8d64\u306e\u77e2\u5370\u306e\u56e0\u679c\u95a2\u4fc2\u304c\u4f5c\u52d5\u3057\u305f\u305f\u3081\u306e\u60c5\u5831\u30d0\u30a4\u30a2\u30b9\u306e\u4e00\u4f8b\u306b\u306a\u308a\u307e\u3059\u3002\u3053\u306e\u3088\u3046\u306a\u30d0\u30a4\u30a2\u30b9\u306f\u4ecb\u5165\u304c\u65b0\u3057\u3044\u6cbb\u7642\u6cd5\u3067\u30a2\u30a6\u30c8\u30ab\u30e0\u6e2c\u5b9a\u8005\u304c\u3088\u308a\u9ad8\u3044\u52b9\u679c\u3092\u671f\u5f85\u3057\u3066\u3044\u308b\u3088\u3046\u306a\u5834\u5408\u306b\u8d77\u304d\u5f97\u307e\u3059\u3002\u3053\u306e\u3088\u3046\u306a\u30d0\u30a4\u30a2\u30b9\u306f\u691c\u51fa\u30d0\u30a4\u30a2\u30b9\u306b\u76f8\u5f53\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u77e2\u5370\u306e\u59cb\u70b9\u306e\u65b9\u304c\u539f\u56e0\u3067\u7d42\u70b9\u306e\u65b9\u304c\u7d50\u679c\u3092\u793a\u3057\u307e\u3059\u3002I\u306fIntervention\u4ecb\u5165\u307e\u305f\u306fE\u3068\u66f8\u3044\u3066Exposure\u8981\u56e0\u66b4\u9732\u3001C\u306fCommon cause\u5171\u901a\u539f\u56e0\uff1dConfounder\u4ea4\u7d61\u56e0\u5b50\u3001O\u306fOutcome\u30a2\u30a6\u30c8\u30ab\u30e0\u3092\u8868\u3057\u307e\u3059\u3002Oi<\/sub>\u306fIntermediate outcome\u4e2d\u9593\u30a2\u30a6\u30c8\u30ab\u30e0\u3001Oe<\/sub>\u306fEndpoint\u30a8\u30f3\u30c9\u30dd\u30a4\u30f3\u30c8\u3067\u3059\u3002I*\u306f\u6e2c\u5b9a\u3055\u308c\u305f\u4ecb\u5165\u3001O*\u306f\u6e2c\u5b9a\u3055\u308c\u305f\u30a2\u30a6\u30c8\u30ab\u30e0\u3092\u8868\u3057\u307e\u3059\u3002U\u306f\u6e2c\u5b9a\u8aa4\u5dee\u3092\u5f15\u304d\u8d77\u3053\u3059\u56e0\u5b50\u3067\u3001\u591a\u304f\u306e\u5834\u5408\u4e0d\u660e\u3067\u3059\u3002<\/p>\n\n\n\n

DAG\u306e\u5404\u5909\u6570<\/strong><\/p>\n\n\n\n

\u3053\u308c\u3089\u3001I, C, O, Oi<\/sub>, Oe<\/sub>, I*, O*, U\u306f\u5909\u6570\u3092\u8868\u3057\u3001\u4f8b\u3048\u3070\u3001I=1\u306f\u4ecb\u5165\u3042\u308a\u3001I=0\u306f\u4ecb\u5165\u306a\u3057\u3001\u306e\u3088\u3046\u306a\u5024\u304c\u8a2d\u5b9a\u3055\u308c\u3001\u4f8b\u3048\u3070O\uff1d\uff11\u6cbb\u7652\u3001O\uff1d\uff10\u975e\u6cbb\u7652\u3068\u3059\u308b\u3068\u3001\u6761\u4ef6\u4ed8\u304d\u78ba\u7387\u306e\u5f0f\u3092\u7528\u3044\u3066P(O=1|I=1)\u3068\u8a18\u8ff0\u3059\u308b\u3068\u3001I\u304c\u4ecb\u5165\u3042\u308a\u306e\u5834\u5408\u306eO\u304c\u6cbb\u7652\u3068\u306a\u308b\u78ba\u7387\u3092\u8868\u3057\u3001\u4ecb\u5165\u7fa4\u306e\u6cbb\u7652\u78ba\u7387\u3092\u8868\u3059\u3053\u3068\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u56f3\u4e2d\u30dc\u30c3\u30af\u30b9\u3067\u56f2\u3093\u3067\u3042\u308b\u306e\u304c\u5b9f\u969b\u306e\u5206\u6790\u5bfe\u8c61\u3068\u306a\u308b\u5909\u6570\u3067\u3059\u3002S\u306f\u9078\u629e\u3092\u8868\u3059\u5909\u6570\u3067\u3059\u304c\u3001S\u306e\u30dc\u30c3\u30af\u30b9\u306e\u610f\u5473\u306f\u3001\u4ecb\u5165\u3068\u4e2d\u9593\u30a2\u30a6\u30c8\u30ab\u30e0\u306b\u57fa\u3065\u304f\u5bfe\u8c61\u8005\u306e\u9664\u5916\u304c\u7814\u7a76\u30c7\u30b6\u30a4\u30f3\u3042\u308b\u3044\u306f\u5206\u6790\u306e\u3057\u304b\u305f\u3067\u8d77\u304d\u308b\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002S\u306e\u5024\u304c\uff10\u306a\u3089\u5bfe\u7167\u30011\u306a\u3089\u4ecb\u5165\u3068\u3044\u3046\u8a2d\u5b9a\u3084\u30010\u306f\u975e\u8131\u843d\u30011\u306f\u8131\u843d\u3001\uff10\u306f\u5831\u544a\u3059\u308b\u30011\u306f\u5831\u544a\u3057\u306a\u3044\u3068\u3044\u3046\u3088\u3046\u306a\u5024\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u5de6\u4e0b\u306e\u5171\u901a\u539f\u56e0\u306eDAG\u306e\u9752\u3044\u70b9\u7dda\u306fI\u2192C\u2192O\u3068\u3044\u3046\u672c\u6765\u306a\u3044\u306f\u305a\u306e\u56e0\u679c\u95a2\u4fc2\u304cBack door path\u30d0\u30c3\u30af\u30c9\u30a2\u7d4c\u8def\u3068\u3057\u3066\u958b\u304b\u308c\u308b\u3068\u3044\u3046\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\u7cfb\u7d71\u7684\u6e2c\u5b9a\u8aa4\u5dee\u306eDAG\u306f\u5fc5\u305a\u3057\u3082\u77e2\u5370\u306e\u3059\u3079\u3066\u304c\u540c\u6642\u306b\u8d77\u304d\u308b\u4e8b\u8c61\u3068\u3044\u3046\u3053\u3068\u3067\u306f\u306a\u304f\u3001\u3069\u306e\u77e2\u5370\u304c\u6709\u52b9\u304b\u306f\u3001\u5206\u6790\u5bfe\u8c61\u306e\u7814\u7a76\u306b\u3088\u3063\u3066\u7570\u306a\u3063\u3066\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u89b3\u5bdf\u7814\u7a76\u306e\u5834\u5408\u306f\u3001I\u3092E\u8981\u56e0\u66dd\u9732\u306b\u7f6e\u304d\u63db\u3048\u307e\u3059\u3002<\/p>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306f\u6570\u591a\u304f\u5b58\u5728\u3057\u3001\u89b3\u5bdf\u7814\u7a76\u306f\u30d0\u30a4\u30a2\u30b9\u306e\u5f71\u97ff\u3092\u53d7\u3051\u3084\u3059\u3044\u3067\u3059\u304c\u3001\u30e9\u30f3\u30c0\u30e0\u5316\u6bd4\u8f03\u8a66\u9a13\u3082\u30d0\u30a4\u30a2\u30b9\u306b\u7121\u7e01\u3067\u306f\u306a\u304f\u3001\u591a\u304f\u306e\u30d0\u30a4\u30a2\u30b9\u306e\u5f71\u97ff\u3092\u53d7\u3051\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u30e9\u30f3\u30c0\u30e0\u5316\u6bd4\u8f03\u8a66\u9a13\u306e\u30d0\u30a4\u30a2\u30b9\u8a55\u4fa1\u306b\u3064\u3044\u3066\u3001\u7279\u306bCochrane risk of bias tool ver. 2.0 RoB 2)\u3092\u4e2d\u5fc3\u306b\u30b9\u30e9\u30a4\u30c9\u3068\u89e3\u8aac\u306e\u8cc7\u6599\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002RoB 2\u3092\u7528\u3044\u305f\u30e9\u30f3\u30c0\u30e0\u5316\u6bd4\u8f03\u8a66\u9a13\u306e\u30a8\u30d3\u30c7\u30f3\u30b9\u8a55\u4fa1\u306e\u4f5c\u696d\u3092\u3059\u308b\u969b\u306b\u53c2\u8003\u306b\u3057\u3066\u304f\u3060\u3055\u3044 \u2192 Link<\/a><\/p>\n\n\n\n

\u6587\u732e\uff1a
Turner RM, Spiegelhalter DJ, Smith GC, Thompson SG: Bias modelling in evidence synthesis. J R Stat Soc Ser A Stat Soc 2009;172:21-47. PMID: 19381328 PubMed<\/a>

Phillippo DM, Dias S, Ades AE, Didelez V, Welton NJ: Sensitivity of treatment recommendations to bias in network meta-analysis. J R Stat Soc Ser A Stat Soc 2018;181:843-867. PMID: 30449954 PubMed<\/a>

Lash TL, VanderWeele TJ, Haneuse S, Rothman KJ: Modern Epidemiology (FORTH EDITION). 2021,  Wolters Kluwer, PA, USA. Amazon<\/a>

Luijendijk HJ, Page MJ, Burger H, Koolman X. Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials. BMC Med Res Methodol. 2020 Sep 23;20(1):237. doi: 10.1186\/s12874-020-01115-7. PubMed<\/a><\/p>\n\n\n\n

Westreich D: Berkson’s bias, selection bias, and missing data. Epidemiology 2012;23:159-64. doi: 10.1097\/EDE.0b013e31823b6296 PMID: 22081062 PubMed<\/a><\/p>\n\n\n\n

Hern\u00e1n MA, Monge S: Selection bias due to conditioning on a collider. BMJ 2023;381:1135. doi: 10.1097\/EDE.0000000000000031 PMID: 37286200 PubMed<\/a><\/p>\n\n\n\n

\u30d0\u30a4\u30a2\u30b9\u306b\u95a2\u3059\u308b\u8ad6\u6587\u306f\u305f\u304f\u3055\u3093\u3042\u308a\u307e\u3059\u304c\u3001\u5f79\u7acb\u3061\u305d\u3046\u306a\u6587\u732e\u3092\u5c11\u3057\u3042\u3052\u3066\u304a\u304d\u307e\u3059\uff1a
Hern\u00e1n MA, Monge S: Selection bias due to conditioning on a collider. BMJ 2023;381:1135. doi: 10.1136\/bmj.p1135 PMID: 37286200 PubMed<\/a><\/p>\n\n\n\n

Sj\u00f6lander A: Selection Bias with Outcome-dependent Sampling. Epidemiology 2023;34:186-191. doi: 10.1097\/EDE.0000000000001567 PMID: 36722800 PubMed<\/a><\/p>\n\n\n\n

Lu H, Cole SR, Howe CJ, Westreich D: Toward a Clearer Definition of Selection Bias When Estimating Causal Effects. Epidemiology 2022;33:699-706. doi: 10.1097\/EDE.0000000000001516 PMID: 35700187 PubMed<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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