{"id":27204,"date":"2021-06-24T21:10:38","date_gmt":"2021-06-24T13:10:38","guid":{"rendered":"https:\/\/swarma.org\/?p=27204"},"modified":"2021-06-24T21:10:38","modified_gmt":"2021-06-24T13:10:38","slug":"%e5%9b%be%e6%a8%a1%e5%9e%8b%e4%b8%8e%e5%9b%a0%e6%9e%9c%e6%8e%a8%e7%90%86%e5%9f%ba%e7%a1%80-scm%e6%a1%86%e6%9e%b6%e5%92%8cdo-calculus","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=27204","title":{"rendered":"\u56fe\u6a21\u578b\u4e0e\u56e0\u679c\u63a8\u7406\u57fa\u7840- SCM\u6846\u67b6\u548cDo-Calculus"},"content":{"rendered":"
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\u5982\u679c\u4f60\u66fe\u7ecf\u4e0a\u8fc7\u8ba1\u91cf\u7ecf\u6d4e\u5b66\u7684\u8bfe\uff0c\u6216\u8005\u9605\u8bfb\u8fc7\u4e4b\u524d\u96c6\u667a\u4ff1\u4e50\u90e8\u53d1\u5e03\u7684<\/span>\u5173\u4e8e\u56e0\u679c\u6548\u5e94\u7684\u6587\u7ae0<\/span><\/a>\uff0c\u6216\u8005\u4f60\u4f1a\u5f88\u81ea\u4fe1\u5730\u8bf4\uff0c\u8fd9\u662f\u4e00\u4e2a\u5178\u578b\u7684\u901a\u8fc7\u89c2\u6d4b\u6570\u636e\u8fdb\u884c\u56e0\u679c\u6548\u5e94\u53d1\u73b0\u53ca\u8bc4\u4f30\u7684\u95ee\u9898\u3002\u4f20\u7edf\u610f\u4e49\u4e0a\uff0c\u901a\u8fc7\u624b\u52a8\u63a8\u5bfc\u548c\u6d4b\u8bd5\u5404\u79cd\u6a21\u578b\uff0c\u6211\u4eec\u53ef\u4ee5\u89e3\u51b3\u5305\u542b\u5c11\u91cf\u53d8\u91cf\u7684\u56e0\u679c\u63a8\u7406\u95ee\u9898\uff0c\u7136\u800c\uff0c\u968f\u7740\u6570\u636e\u79d1\u5b66\u7684\u5174\u8d77\uff0c\u6211\u4eec\u73b0\u5728\u5f80\u5f80\u9700\u8981\u4ece\u4e00\u4e2a\u5305\u542b\u6210\u767e\u4e0a\u5343\u53d8\u91cf\u7684\u6570\u636e\u96c6\u4e2d\u63a8\u65ad\u548c\u8bc4\u4f30\u56e0\u679c\u6548\u5e94\uff0c\u53d8\u91cf\u7684\u5173\u7cfb\u9519\u7efc\u590d\u6742\uff0c\u56e0\u6b64\uff0c<\/span>\u4e00\u4e2a\u53ef\u4ee5\u81ea\u52a8\u5316\u8fdb\u884c\u56e0\u679c\u63a8\u7406\u7684\u6f14\u7b97\u5e94\u7528\u6846\u67b6 \u2013 \u7ed3\u6784\u56e0\u679c\u6a21\u578b\uff08Structural Causal Model \uff09<\/span>\u53cado-calculus<\/span><\/a>\u5e94\u8fd0\u800c\u751f\u3002\u672c\u6587\u65e8\u5728\u901a\u8fc7\u5b9e\u4f8b\u53ca\u6a21\u62df\u6570\u636e\uff0c\u4e32\u8bb2Judea Pearl\u7684\u56e0\u679c\u7406\u8bba\u57fa\u7840\u77e5\u8bc6\u3002<\/span><\/p>\n


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1. \u641e\u526f\u4e1a\u4f1a\u5f71\u54cd\u4f60\u7684\u4e3b\u4e1a\u5417\uff1f<\/strong><\/strong><\/p>\n

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Figure 1 \u53d8\u91cf\u6982\u89c8<\/span><\/p>\n


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earningsMain<\/span><\/em>=\uff08\u03b2<\/span><\/em>0<\/sub><\/span>+\u03b2<\/span><\/em>\uff091<\/sub><\/span>sidelineTime<\/em>+\u03b2<\/span><\/em>2<\/sub><\/span>edu<\/em>+\u03b2<\/span><\/em>3<\/sub><\/span>hangout<\/em>+\u03b2<\/span><\/em>4<\/sub><\/span>openness<\/em>+\u03b2<\/span><\/em>5<\/sub><\/span>friendsSideline<\/em>+\u03b2<\/span><\/em>6<\/sub><\/span>sidelineInvest<\/em>+<\/span>\u03b5<\/span><\/em><\/span><\/span><\/p>\n


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\t\u7136\u540e\u4f60\u5f97\u51fa\u7ed3\u8bba\uff0c\u5176\u4ed6\u6761\u4ef6\u4e0d\u53d8\u7684\u60c5\u51b5\u4e0b\uff0c\u6bcf\u4e00\u4e2a\u5355\u4f4dsidelineTim<\/em>\u7684\u53d8\u52a8\uff0c\u4f1a\u5f15\u8d77\u03b2<\/span><\/em>1<\/sub><\/span>\u4e2a\u5355\u4f4dearnings<\/em>\u7684\u53d8\u52a8\u3002\u4f46\u662f\uff0c\u8fd9\u4e2a\u7ed3\u8bba\u771f\u7684\u6b63\u786e\u3001\u65e0\u504f\u3001\u5177\u6709\u56e0\u679c\u6027\u5417\uff1f\u5bf9\u4e8e\u6570\u636e\u4e2d\u7684\u6bcf\u4e00\u4e2a\u53d8\u91cf\uff0c\u6211\u4eec\u662f\u5426\u53ef\u4ee5\u201c\u65e0\u8111\u201d\u628a\u5b83\u4eec\u90fd\u52a0\u8fdb\u6a21\u578b\u91cc\u5462\uff1f<\/span><\/p>\n


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\u6211\u4eec\u53ef\u4ee5\u7528\u4e00\u4e9b\u6a21\u62df\u6570\u636e\u8fdb\u884c\u9a8c\u8bc1\uff1a\u5047\u5982\u6211\u4eec\u5f00\u4e86\u201c\u4e0a\u5e1d\u4e4b\u773c\u201d\uff0c\u77e5\u9053\u4e16\u95f4\u4e07\u4e8b\u4e07\u7269\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u5305\u62ec\u56e0\u679c\u65b9\u5411\u53ca\u5176\u5f71\u54cd\u5927\u5c0f\uff0c\u6211\u4eec\u5047\u8bbe\u4ee5\u4e0a\u53d8\u91cf\u670d\u4ece\u4ee5\u4e0b\u56e0\u679c\u5173\u7cfb<\/span>\uff08\u8bf7\u6ce8\u610f\u4e0b\u56fe\u4e2d\u7684\u7bad\u5934\u6307\u5411\uff09<\/span>\uff1a<\/span><\/p>\n


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Figure 2 \u53d8\u91cf\u56e0\u679c\u5173\u7cfb\u56fe<\/span><\/p>\n


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\u8be5\u56fe\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u526f\u4e1a\u65f6\u95f4\u6295\u5165<\/span>\uff08sidelineTime<\/em>\uff09<\/span>\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165<\/span>\uff08earningsMain<\/em>\uff09<\/span>\u6709\u56e0\u679c\u5f71\u54cd\u3002\u5177\u4f53\u6765\u8bb2\uff0c\u526f\u4e1a\u65f6\u95f4\u6295\u5165\u6536\u5230\u8eab\u8fb9\u505a\u526f\u4e1a\u670b\u53cb\u7684\u6570\u91cf<\/span>\uff08friendsSideline<\/em>\uff09<\/span>\u548c\u4e2a\u4f53\u6559\u80b2\u80cc\u666f<\/span>\uff08edu<\/em>\uff09<\/span>\u7684\u5f71\u54cd\uff1b\u4e3b\u4e1a\u6536\u5165\u6536\u5230\u6559\u80b2\u80cc\u666f\u548c\u4e2a\u4f53\u6027\u683c\u5f00\u653e\u6027<\/span>\uff08openness<\/em>\uff09<\/span>\u7684\u5f71\u54cd\uff1b\u526f\u4e1a\u65f6\u95f4\u6295\u5165\u6536\u5230\u8eab\u8fb9\u505a\u526f\u4e1a\u670b\u53cb\u7684\u6570\u91cf<\/span>\uff08friendsSideline<\/em>\uff09<\/span>\u548c\u4e2a\u4f53\u6027\u683c\u5f00\u653e\u6027<\/span>\uff08openness<\/em>\uff09<\/span>\u4f1a\u5f71\u54cd\u4e00\u4e2a\u4eba\u5e73\u5747\u6bcf\u5468\u53ef\u4ee5\u7ed3\u8bc6\u65b0\u670b\u53cb\u7684\u6570\u91cf<\/span>\uff08newFriendsPerWeek<\/em>\uff09<\/span>\uff0c\u4f46\u7ed3\u4ea4\u65b0\u670b\u53cb\u6570\u91cf\u5bf9\u4e8e\u526f\u4e1a\u65f6\u95f4\u6295\u5165<\/span>\uff08sidelineTime<\/em>\uff09<\/span>\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165<\/span>\uff08earningsMain<\/em>\uff09<\/span>\u90fd\u6ca1\u6709\u76f4\u63a5\u56e0\u679c\u5f71\u54cd\uff1b\u6700\u540e\uff0c\u526f\u4e1a\u65f6\u95f4\u6295\u5165<\/span>\uff08sidelineTime<\/em>\uff09<\/span>\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165<\/span>\uff08earningsMain<\/em>\uff09<\/span>\u5747\u5bf9\u526f\u4e1a\u8bbe\u5907\u5347\u7ea7\u6295\u5165<\/span>\uff08sidelineInvest<\/em>\uff09<\/span>\u6709\u56e0\u679c\u5f71\u54cd\u3002<\/span><\/p>\n


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\u6211\u4eec\u9996\u5148\u5728R\u4e2d\u751f\u6210\u4e00\u4e9b\u865a\u62df\u6570\u636e\uff0c\u5982\u56fe4\u548c\u56fe5\u6240\u793a\u3002\u4e0d\u8fc7\u5177\u4f53\u4ee3\u7801\u4e0d\u91cd\u8981\uff0c\u91cd\u8981\u7684\u662f\uff1a<\/span><\/p>\n


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\uff081\uff09\u6211\u4eec\u73b0\u5728\u5f00\u4e86\u4e0a\u5e1d\u4e4b\u773c\uff0c\u547d\u4ee4sidelineTime\u548cearningMain\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u4e3a\u6b63\u5411\uff0c\u4e14\u5927\u5c0f\u4e3a1.2\uff0c\u5373\u5176\u4ed6\u6761\u4ef6\u4e0d\u53d8\u7684\u60c5\u51b5\u4e0b\uff0csidelineTime\u6bcf\u589e\u957f\u4e00\u5355\u4f4d\uff0c\u4e3b\u4e1a\u6536\u5165\u589e\u52a01.2\u4e2a\u5355\u4f4d\uff1a<\/span><\/p>\n


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earningsMain<\/span><\/em>=1.2sidelineTime<\/span><\/em>+0.6edu<\/em>+0.3openness<\/em>+\u03b5<\/span><\/em><\/span>
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\uff082\uff09\u7c7b\u4f3c\u5730\uff0c\u6211\u4eec\u4e5f\u5b9a\u4e49\u4e86\u5176\u4ed6\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u8868\u793a\u53d8\u91cf\u4e4b\u95f4\u76f8\u4e92\u56e0\u679c\u5173\u7cfb\u7684\u7cfb\u6570\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/span><\/p>\n


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Figure 3 \u53d8\u91cf\u56e0\u679c\u5173\u7cfb\u56fe\uff0c\u542b\u7cfb\u6570<\/span><\/p>\n


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Figure 4 \u7528R\u751f\u6210\u6a21\u62df\u6570\u636e<\/span><\/p>\n


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Figure 5 \u6a21\u62df\u6570\u636e\u6982\u89c8<\/span><\/p>\n


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\uff083\uff09\u56e0\u4e3a\u6570\u636e\u662f\u6211\u4eec\u751f\u6210\u7684\uff0c\u6211\u4eec\u5f00\u4e86\u201c\u4e0a\u5e1d\u4e4b\u773c\u201d\uff0c\u77e5\u9053\u6211\u4eec\u5173\u7cfb\u7684\u56e0\u679c\u5173\u7cfb\u5927\u5c0f\u4e3a1.2\u3002\u90a3\u4e48\uff0c\u5728\u6240\u6709\u53ef\u80fd\u7684\u6a21\u578b\u91cc\uff0c\u53ea\u6709\u6700\u7ec8\u7b49\u4e8e\u6216\u8005\u65e0\u9650\u63a5\u8fd11.2\u8fd9\u4e2a\u6570\u503c\u7684\u6a21\u578b\u624d\u662f\u6700\u53ef\u80fd\u6b63\u786e\u7684\u6a21\u578b\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u53ea\u6709\u6b63\u786e\u7684\u6dfb\u52a0\u53d8\u91cf\u5728\u6a21\u578b\u4e2d\uff0c\u6211\u4eec\u624d\u80fd\u5f97\u5230\u6b63\u786e\u7684\u56e0\u679c\u5173\u7cfb\u4f30\u8ba1\u3002<\/span><\/p>\n


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\u73b0\u5728\u6211\u4eec\u518d\u6765\u95ee\u4e00\u6b21\uff0c\u5982\u679c\u6211\u4eec\u5df2\u7ecf\u77e5\u9053\u4e86\u6240\u6709\u7684\u8fd9\u4e9b\u56e0\u679c\u5173\u7cfb\u5bfc\u5411\uff0c\u4f60\u8ba4\u4e3a\u54ea\u4e9b\u53d8\u91cf\u5e94\u8be5\u88ab\u653e\u5165\u6a21\u578b\u4e2d\uff1f\u5728\u4e0b\u5217\u8fd9\u4e9b\u53ef\u80fd\u7684\u6a21\u578b\u4e2d\uff0c\u4f60\u8ba4\u4e3a\u54ea\u4e2a\u6a21\u578b\u662f\u5408\u9002\u7684\uff1f<\/span><\/strong><\/span><\/p>\n


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Figure 6 \u53ef\u4f9b\u9009\u62e9\u7684\u4e00\u4e9b\u6a21\u578b<\/span><\/p>\n


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\u53ef\u4ee5\u770b\u5230\uff0c\u6a21\u578b\uff081\uff09\u662f\u6700\u57fa\u7840\u7684\u9009\u62e9\uff0c\u4f46\u662f\u53ea\u5305\u62ecsidelineTime\uff0c\u800c\u5ffd\u7565\u5176\u4ed6\u5bf9earningsMain\u6709\u56e0\u679c\u5f71\u54cd\u7684\u53d8\u91cf\uff0c\u4f1a\u5bfc\u81f4\u9ad8\u4f30sidelineTime\u5bf9earningsMain\u7684\u5f71\u54cd\uff1b\u76f8\u53cd\uff0c\u6a21\u578b\uff082\uff09\u5c06\u6240\u6709\u7684\u53ef\u7528\u53d8\u91cf\u90fd\u653e\u8fdb\u6a21\u578b\u4e2d\uff0c\u4e0d\u4f46\u6ca1\u6709\u5e26\u6765\u6709\u6548\u4fe1\u606f\uff0c\u53cd\u800c\u589e\u52a0\u4e86\u66f4\u591a\u7684\u5e72\u6270<\/span>\uff08noise\uff09<\/span>\uff0c\u7ed3\u679c\u4f30\u8ba1\u4e5f\u4e0d\u51c6\u786e\uff1b\u6b64\u5904\u5217\u4e3e\u56db\u4e2a\u6bd4\u8f83\u6709\u4ee3\u8868\u6027\u7684\u6a21\u578b\u53ca\u5176\u7ed3\u679c\uff0c\u7ea2\u8272\u65b9\u6846\u5708\u51fa\u4e86\u8be5\u6a21\u578b\u4e0b\u5bf9\u4e8esidelineTime\u5bf9\u4e8eearningsMain\u7684\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\uff0c\u5176\u4e2d\uff0c\u8d8a\u63a5\u8fd11.2\u771f\u5b9e\u503c\u8868\u793a\u8be5\u6a21\u578b\u8d8a\u63a5\u8fd1\u201c\u771f\u76f8\u201d\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u6211\u4eec\u4f1a\u5f88\u81ea\u7136\u5730\u60f3\u5230\u628a\u6709\u6307\u5411earningsMain\u7684\u53d8\u91cf\u4eec\u90fd\u52a0\u5165\u5230\u6a21\u578b\u91cc\uff0c\u4e8b\u5b9e\u4e0a\uff0c\u5982\u4e0b\u56fe\u6240\u793a\uff0c\u8fd9\u6837\u5f97\u5230\u7684\u7ed3\u679c\u975e\u5e38\u63a5\u8fd1\u771f\u5b9e\u503c1.2\uff1a<\/span><\/p>\n


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Figure 7 \u6a21\u578b(4)\u5bf9\u5e94\u7684\u7ed3\u679c<\/span><\/p>\n


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\t\u7136\u800c\uff0c\u4e00\u65e6\u5728\u6a21\u578b\u4e2d\u52a0\u5165\u4e86\u201csidelineInvest\u201d\uff0c\u9884\u671f\u7684\u56e0\u679c\u6548\u5e94\u53d8\u6210\u4e860.3317\uff0c\u88ab\u4e25\u91cd\u4f4e\u4f30\u4e86\uff1a<\/span><\/p>\n


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Figure 8 \u6a21\u578b\uff085\uff09\u5bf9\u5e94\u7684\u7ed3\u679c<\/span><\/p>\n


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\u6b64\u5916\uff0c\u5373\u4f7f\u5c11\u52a0\u4e00\u4e9b\u3001\u6216\u8005\u591a\u52a0\u4e00\u4e9b\u53d8\u91cf\uff0c\u4f3c\u4e4e\u4e5f\u5bf9\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\u7684\u7ed3\u679c\u6ca1\u6709\u4ea7\u751f\u5f88\u5927\u5f71\u54cd\uff1a\u4f8b\u5982\u56fe8\uff08a\uff09s\u53bb\u6389\u4e86openness\uff0c\u53ea\u4fdd\u7559\u4e86edu\u4f5c\u4e3a\u534f\u53d8\u91cf\uff0c\u7ed3\u679c\u4f30\u8ba1\u4f9d\u7136\u975e\u5e38\u63a5\u8fd11.2\u7684\u771f\u5b9e\u503c\uff1b\u800c\u56fe8\uff08b\uff09-\uff08d\uff09\u5f15\u5165\u4e86\u5176\u4ed6\u7684\u975e\u76f4\u63a5\u4e0e\u4e3b\u4e1a\u6536\u5165\u76f8\u5173\u7684\u53d8\u91cf<\/span>\uff08\u5982hangout\uff0cfriendsSideline\uff09<\/span>\uff0c\u4ed6\u4eec\u7684\u7ed3\u679c\u867d\u7136\u4e0d\u540c\u7a0b\u5ea6\u5730\u79bb1.2\u771f\u5b9e\u503c\u6709\u66f4\u5927\u7684\u504f\u5dee\uff0c\u4f46\u57fa\u672c\u8fd8\u7b97\u51c6\u786e\u3002\u4f46\u4e3a\u4ec0\u4e48\u8fd9\u4e9b\u6a21\u578b\u4e5f\u57fa\u672c\u53ef\u4ee5\u6ee1\u8db3\u6211\u4eec\u5bf9\u4e8e\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\u7684\u9700\u6c42\u5462\uff1f<\/strong><\/span><\/p>\n


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Figure 8 (a)<\/span><\/p>\n<\/td>\n

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Figure 8 (b)<\/span><\/p>\n<\/td>\n<\/tr>\n

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Figure 8 (c)<\/span><\/p>\n<\/td>\n

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Figure 8 (d)<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Figure 9 \u90e8\u5206\u6a21\u578b\u7ed3\u679c\uff0c\u4ece\u5de6\u4e0a\u5230\u53f3\u4e0b\u5206\u522b\u5bf9\u5e94\u6a21\u578b3,6,7,8<\/span><\/p>\n


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\u7136\u800c\uff0c\u6a21\u578b\uff088\uff09\uff0c\u4e5f\u662f\u53bb\u6389\u4e86openness\uff0c\u52a0\u4e0a\u4e86hangout\uff0c\u5374\u5bfc\u81f4\u56e0\u679c\u6548\u5e94\u7684\u4f30\u8ba1\u7ed3\u679c\u9661\u7136\u589e\u52a0\u52301.261960\uff0c\u8ddd\u79bb\u771f\u5b9e\u503c\u51fa\u73b0\u4e86\u5de8\u5927\u7684\u504f\u5dee\uff0c\u8fd9\u53c8\u662f\u4ec0\u4e48\u5462\uff1f<\/span><\/strong><\/span><\/p>\n


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Figure 10 \u6a21\u578b\uff088\uff09\u5bf9\u5e94\u7684\u7ed3\u679c\uff1a\u51fa\u73b0\u4e86\u5f88\u5927\u7684\u4f30\u8ba1\u504f\u5dee<\/span><\/p>\n


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\u8ba9\u6211\u4eec\u6682\u65f6\u4fdd\u7559\u8fd9\u4e24\u4e2a\u7591\u95ee\u3002\u8fd9\u4e2a\u4f8b\u5b50\u8fd8\u53ef\u4ee5\u53d8\u5f97\u66f4\u590d\u6742\u4e00\u70b9\uff1a\u73b0\u5b9e\u751f\u6d3b\u4e2d\uff0c\u6709\u5f88\u591a\u53d8\u91cf\u90fd\u4e0d\u53ef\u89c2\u6d4b\uff0c\u6216\u8005\u4e0d\u597d\u6d4b\u91cf\uff0c\u6bd4\u5982\u5728\u672c\u4f8b\u4e2d\uff0c\u5f00\u5c55\u526f\u4e1a\u7684\u670b\u53cb\u6570\u91cf\u4e0d\u4fbf\u7edf\u8ba1\uff0c\u5bf9\u4e8e\u6027\u683c\u5f00\u653e\u6027\u7684\u6d4b\u8bd5\u4e5f\u96be\u4ee5\u5927\u89c4\u6a21\u83b7\u53d6\uff0c\u5728\u56fe10\u4e2d\uff0c\u6211\u4eec\u7528\u865a\u7ebf\u5706\u5708\u8868\u793a\u8fd9\u4e24\u4e2a\u53d8\u91cf\u73b0\u5728\u6210\u4e3a\u4e86\u4e0d\u53ef\u89c2\u6d4b\u7684\u53d8\u91cf\uff0c\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53c8\u8be5\u5982\u4f55\u6b63\u786e\u4f30\u8ba1\u5f00\u5c55\u526f\u4e1a\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165\u7684\u56e0\u679c\u5173\u7cfb\u5462\uff1f<\/strong><\/span><\/p>\n


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Figure 11 \u56e0\u679c\u5173\u7cfb\u56fe\uff0c\u73b0\u5728\u201c\u597d\u53cb\u505a\u526f\u4e1a\u6570\u91cf\u201d\u548c\u201c\u6027\u683c\u5f00\u653e\u6027\u201d\u53d8\u6210\u4e86\u4e0d\u53ef\u89c2\u6d4b\u7684\u9690\u53d8\u91cf<\/span><\/section>\n


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\u6b64\u65f6\uff0c\u7531\u4e8efriendsSideline\u548copenness\u53d8\u6210\u4e86\u9690\u53d8\u91cf\uff0c\u6211\u4eec\u76ee\u524d\u53ef\u9009\u62e9\u7684\u534f\u53d8\u91cf\u8fd8\u5269\u4e0bedu\uff0changout\uff0c\u548csidelineInvest\u4e09\u4e2a\u3002\u9996\u5148\uff0c\u6211\u4eec\u5c1d\u8bd5\u628ahangout\u52a0\u8fdb\u6a21\u578b\u91cc\uff0c\u540c\u4e4b\u524d\u4e00\u6837\uff0c\u6211\u4eec\u4f1a\u53d1\u73b0\u6b64\u65f6\u4f30\u8ba1\u7684\u7ed3\u679c\u51fa\u73b0\u4e86\u5f88\u5927\u7684\u8bef\u5dee\uff0c\u4ece1.20\u5230\u4e861.26\u3002\u53cd\u800c\u628ahangout\u53bb\u6389\uff0c\u5982\u56fe13\u6240\u793a\uff0c\u4f7f\u5f97\u6211\u4eec\u5728\u6709\u4e0d\u53ef\u89c2\u6d4b\u53d8\u91cf\u7684\u60c5\u51b5\u4e0b\u4f9d\u7136\u5f97\u5230\u4e86\u8fd1\u4f3c\u65e0\u504f\u7684\u4f30\u8ba1\u3002\u8fd9\u4e2a\u4f8b\u5b50\u544a\u8bc9\u6211\u4eec\uff0c\u5373\u4f7f\u6709\u4e9b\u53d8\u91cf\u662f\u65e0\u6cd5\u89c2\u6d4b\u3001\u6ca1\u6709\u83b7\u53d6\u7684\uff0c\u6211\u4eec\u4f9d\u7136\u6709\u529e\u6cd5\u53ef\u4ee5\u6b63\u786e\u63a8\u65adT\u5230Y\u7684\u56e0\u679c\u6548\u5e94\u3002<\/span><\/p>\n


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Figure 12 \u4ece\u4e8b\u526f\u4e1a\u597d\u53cb\u6570\u91cf\u548c\u6027\u683c\u5f00\u653e\u5ea6\u4e0d\u53ef\u89c2\u6d4b\u7684\u60c5\u51b5\u4e0b\uff0c\u6a21\u578b\u4f30\u8ba1\u7ed3\u679c1\uff1a\u52a0\u5165hangout\u8fd9\u4e00\u53d8\u91cf\u4f7f\u5f97\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\u7ed3\u679c\u51fa\u73b0\u8f83\u5927\u504f\u5dee<\/span><\/section>\n


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Figure 13 \u6b64\u6a21\u578b\u4e2d\uff0c\u867d\u7136\u4ece\u4e8b\u526f\u4e1a\u597d\u53cb\u6570\u91cf\u548c\u6027\u683c\u5f00\u653e\u5ea6\u4e0d\u53ef\u89c2\u6d4b\uff0c\u8be5\u6a21\u578b\u4f9d\u7136\u76f8\u5bf9\u51c6\u786e\u5730\u4f30\u8ba1\u4e86\u526f\u4e1a\u6295\u5165\u65f6\u95f4\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165\u7684\u56e0\u679c\u6548\u5e94<\/span>
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\t\u5728\u672c\u4f8b\u4e2d\uff0c\u6211\u4eec\u7684\u76ee\u6807\u662f\u4f30\u8ba1\u4ece\u4e8b\u526f\u4e1a\u5bf9\u4e8e\u4e3b\u4e1a\u6536\u5165\u7684\u56e0\u679c\u6548\u5e94\u3002\u901a\u8fc7\u4e0d\u540c\u7684\u6a21\u578b\u7ed3\u679c\uff0c\u6211\u4eec\u53ef\u4ee5\u4f53\u4f1a\u5230\uff0c\u5728\u5b9e\u9645\u6570\u636e\u5206\u6790\u8fc7\u7a0b\u4e2d\uff0c\u662f\u5426\u9009\u62e9\u67d0\u4e00\u4e2a\u6216\u4e00\u7ec4\u534f\u53d8\u91cf\uff0c\u4f1a\u5bf9\u56e0\u679c\u6548\u5e94\u7684\u4f30\u8ba1\u7ed3\u679c\u4ea7\u751f\u5f88\u5927\u7684\u5f71\u54cd\u3002\u90a3\u4e48\uff0c\u5728\u4e0d\u77e5\u9053\u6570\u636e\u5b9e\u9645\u751f\u6210\u8fc7\u7a0b\u7684\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u8be5\u5982\u4f55\u9009\u62e9\u53d8\u91cf\u3001\u8fdb\u884c\u6b63\u786e\u7684\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\u5462\uff1f\u6709\u6ca1\u6709\u4e00\u4e9b\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5224\u65ad\u5462\uff1f\u5982\u679c\u6709\u7684\u8bdd\uff0c\u8fd9\u4e9b\u6280\u5de7\u5728\u4e0d\u53ef\u89c2\u6d4b\/\u9690\u53d8\u91cf\u5b58\u5728\u7684\u60c5\u51b5\u4e0b\uff0c\u8fd8\u6210\u7acb\u5417\uff1f\u6b64\u5916\uff0c\u672c\u4f8b\u4e2d\u4ec5\u67097\u4e2a\u53d8\u91cf\uff0c\u53ea\u8003\u8651\u4e00\u9636\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u7684\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u5df2\u7ecf\u670932\u79cd\u53ef\u80fd\u7684\u6a21\u578b\uff0c\u5728\u5904\u7406\u5e9e\u5927\u6570\u636e\u5e93\u65f6\uff0c\u6211\u4eec\u9700\u8981\u66f4\u52a0\u81ea\u52a8\u5316\u7684\u65b9\u6cd5\u5e2e\u52a9\u6211\u4eec\u9009\u62e9\u53d8\u91cf\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528\u56fe\u6a21\u578b\u3001\u56e0\u679c\u7ed3\u679c\u6a21\u578b\u548cdo- calculus\u6765\u5e2e\u52a9\u6211\u4eec\u89e3\u7b54\u8fd9\u4e9b\u95ee\u9898\u3002<\/span><\/p>\n<\/p>\n


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2. \u56fe\u6a21\u578b\u548c\u56e0\u679c\u7ed3\u6784\u6a21\u578b<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


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\t\u5176\u5b9e\uff0c\u5927\u5bb6\u5df2\u7ecf\u5728\u521a\u624d\u7684\u4f8b\u5b50\u4e2d\u5f00\u59cb\u4e0d\u77e5\u4e0d\u89c9\u5730\u8ba4\u8bc6\u4e86\u56fe\u6a21\u578b\u548c\u56e0\u679c\u7ed3\u679c\u6a21\u578b\u4e86\u3002\u76f8\u6bd4\u4e8e\u770b\u7740\u6240\u6709\u7684\u53d8\u91cf\u548c\u516c\u5f0f\uff0c\u753b\u56fe\u4f7f\u5f97\u53d8\u91cf\u7684\u56e0\u679c\u5173\u7cfb\u76f4\u89c2\u5730\u5448\u73b0\uff0c\u8fd9\u4e9b\u56fe\u53eb\u505aCasual graphs<\/span>\uff08\u56e0\u679c\u56fe\uff09<\/span>\u3002\u4ed6\u4eec\u8fd8\u6709\u4e2a\u66f4\u901a\u7528\u7684\u540d\u5b57\u2014\u2014\u6709\u5411\u65e0\u73af\u56fe<\/span>\uff08DAG, Directed Acyclic Graph\uff09<\/span>\u3002\u6bd4\u5982\uff0c\u56fe14\u5c55\u793a\u4e86\u672c\u6587\u4f8b\u5b50\u4e2d\u7684\u53d8\u91cf\u56e0\u679c\u7ed3\u6784\uff0c\u6574\u5f20\u56fe\u7531\u9876\u70b9<\/span>\uff08\u53d8\u91cf\uff09<\/span>\u548c\u8fde\u63a5\u8fd9\u4e9b\u9876\u70b9\u7684\u8fb9<\/span>\uff08\u8868\u793a\u56e0\u679c\u5173\u7cfb\uff09<\/span>\u7ec4\u6210\u3002\u7bad\u5934\u4ee3\u8868\u56e0\u679c\u5173\u7cfb\u7684\u65b9\u5411\uff0c\u6bd4\u5982T\u6307\u5411Y\uff0c\u8868\u793aT\u5bf9Y\u7684\u539f\u56e0\uff0cY\u662fT\u7684\u7ed3\u679c\u3002T\u53c8\u53ef\u4ee5\u6210\u4e3aY\u7684\u7236\u8f88<\/span>\uff08parent\uff09<\/span>\uff0cY\u53c8\u53ef\u4ee5\u6210\u4e3aT\u7684\u5b50\u8f88<\/span>\uff08child\uff09<\/span>\u3002\u7136\u800c\uff0c\u8fd9\u4e9b\u56e0\u679c\u5173\u7cfb\u5e76\u4e0d\u4e00\u5b9a\u4e00\u4e00\u5bf9\u5e94\u3002\u4f8b\u5982\uff0cT\u6709\u4e24\u4e2a\u7236\u8f88\uff0c\u5206\u522b\u662fU1\u548cW\uff1b\u540c\u65f6\uff0cT\u4e5f\u6709\u4e24\u4e2a\u5b50\u8f88\uff0c\u5206\u522b\u662fY\u548cZ\u3002\u6b63\u662f\u56e0\u4e3a\u4e16\u95f4\u4e07\u7269\u4e92\u76f8\u5173\u8054\u3001\u4e92\u76f8\u4f5c\u7528\uff0c\u624d\u4f7f\u5f97\u7eaf\u7cb9\u5730\u4f30\u8ba1\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u6548\u5e94\u53d8\u5f97\u5341\u5206\u5177\u6709\u6311\u6218\u6027\/\u6709\u4e50\u8da3\u3002\u901a\u4fd7\u5730\u8bf4\uff0c\u63a2\u7d22T\u5bf9Y\u56e0\u679c\u6548\u5e94\u7684\u8fc7\u7a0b\uff0c\u5c31\u662f\u628a\u8fd9\u4e24\u8005\u4e4b\u95f4\u7684\u5176\u4ed6\u5e72\u6270\u53d8\u91cf<\/span>\uff08confounder\uff09<\/span>\u7684\u4f5c\u7528\u90fd\u5254\u9664\u7684\u8fc7\u7a0b\u3002<\/span><\/p>\n

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Figure 14 \u4e00\u4e2a\u56e0\u679c\u56fe\u7684\u4f8b\u5b50<\/span><\/p>\n


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\t\u4e3a\u4e86\u7528\u66f4\u7b80\u6d01\u7684\u8bed\u8a00\u548c\u7b26\u53f7\u8868\u793a\u56e0\u679c\u56fe\uff0c\u53ca\u5176\u53d8\u91cf\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u6211\u4eec\u89c4\u5b9a\uff1a<\/span><\/p>\n


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\u56e0\u679c\u56fe\u7528G\u8868\u793a\uff0c\u4e00\u822c\u6765\u8bf4\uff0c\u611f\u5174\u8da3\u7684\u81ea\u53d8\u91cf\u8bb0\u505aX\u6216\u8005T\uff0c\u56e0\u53d8\u91cf\u53ef\u4ee5\u8bb0\u4f5cZ\u6216\u8005Y\uff1b<\/span>\u5982\u56fe15\uff0c\u6211\u4eec\u6709\u4e86\u4e00\u4e2a\u56e0\u679c\u56feG\uff0c\u4e00\u5bf9\u6211\u4eec\u611f\u5174\u8da3\u7684X\u5bf9Z\u7684\u56e0\u679c\u6548\u5e94\uff0c\u4ee5\u53ca\u5176\u4ed6\u56db\u4e2a\u534f\u53d8\u91cfW1-W4\u3002\u5982\u679c\u6211\u4eec\u5c06\u56fe\u4e2d\u7684\u6240\u6709\u4eceX\u51fa\u53d1\u7684\u7bad\u5934\u7684\u5220\u9664<\/span>\uff08\u5373\u5220\u9664X\u7684\u6240\u6709\u5b50\u8f88\uff09<\/span>\uff0c\u6211\u4eec\u5c06\u5f97\u5230\u7684\u65b0\u56fe\u8bb0\u4f5c<\/span>\uff08\u56fe16\u5de6\uff09<\/span>\uff1b\u7c7b\u4f3c\u7684\uff0c\u5982\u679c\u5c06\u56fe\u4e2d\u6240\u6709\u5c04\u5411X\u7684\u7bad\u5934\u5220\u9664<\/span>\uff08\u5373\u5220\u9664X\u7684\u6240\u6709\u7236\u8f88\uff09<\/span>\uff0c\u6211\u4eec\u5c06\u5f97\u5230\u7684\u65b0\u56fe\u8bb0\u4f5c<\/span>\u3002\u540c\u7406\uff0c\u5982\u679c\u5c06\u56fe\u4e2d\u6240\u6709\u5c04\u5411X\u7684\u7bad\u5934\u5220\u9664\uff0c\u5c06\u6240\u6709\u4eceZ\u5c04\u51fa\u7684\u7bad\u5934\u5220\u9664\uff0c\u5f97\u5230\u7684\u65b0\u56fe\u8bb0\u4f5c<\/span>\u3002<\/span><\/p>\n

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Figure 15 \u56e0\u679c\u56fe\u793a\u4f8b<\/span><\/p>\n


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Figure 16 \u56e0\u679c\u56fe<\/span><\/p>\n


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\u82e5\u60f3\u8981\u8868\u8fbe\u4e24\u53d8\u91cfA\uff0cB\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u6211\u4eec\u89c4\u5b9a\u4f7f\u7528\uff1a<\/span><\/p>\n


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\u533a\u522b\u4e8e\u4e00\u822c\u7684\u7b49\u53f7\uff0cB = A \u548cA = B\u662f\u540c\u4e00\u4e2a\u610f\u601d\uff1b\u5728\u8fd9\u91cc\uff0c:= \u4ee3\u8868\u56e0\u679c\u5173\u7cfb\uff0c\u5373A\u662fB\u7684\u4e00\u4e2a\u539f\u56e0\u3002\u5f53\u7136\uff0c\u4e00\u822c\u60c5\u51b5\u4e0b\uff0cB\u5f80\u5f80\u53ef\u80fd\u6709\u591a\u4e2a\u539f\u56e0\uff0c\u5e76\u4e14\u6709\u5f88\u591a\u539f\u56e0\u662f\u672a\u77e5\u7684\uff0c\u6216\u8005\u5df2\u77e5\u4f46\u65e0\u6cd5\u6d4b\u91cf\u7684\uff0c\u8fd9\u65f6\u5019\uff0c\u6211\u4eec\u7528U\u4ee3\u8868\u65e0\u6cd5\u89c2\u6d4b\u6216\u672a\u77e5\u7684\u53d8\u91cf\u3002\u5982\u4e0b\u56fe\u6240\u793a\uff0c\u5bf9\u5e94\u7684\u7ed3\u6784\u65b9\u7a0b\u4e3a\uff1a<\/span><\/p>\n


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\u5f53\u591a\u4e2a\u65b9\u7a0b\u7ec4\u5408\u5728\u4e00\u8d77\uff0c\u53ef\u4ee5\u5b8c\u6574\u4ee3\u8868\u4e00\u4e2a\u56e0\u679c\u56fe\u7684\u4fe1\u606f\u65f6\uff0c\u6211\u4eec\u4fbf\u83b7\u5f97\u4e86\u7ed3\u6784\u56e0\u679c\u6a21\u578b<\/span>\uff08SCMs, Structural causal model\uff09<\/span>\u3002\u5982\u4e0b\u56fe\uff0c\u7ed3\u6784\u56e0\u679c\u6a21\u578bM\u4e2d\u6709\u4e09\u4e2a\u7ed3\u6784\u65b9\u7a0b\uff0c\u5206\u522b\u4ee3\u8868\u4e86\u53d8\u91cfB\u3001C\u3001D\u7684\u56e0\u3002\u7b80\u8a00\u4e4b\uff0c\u7ed3\u6784\u56e0\u679c\u6a21\u578b\u53ef\u4ee5\u8bf4\u662f\u56e0\u679c\u56fe\u7684\u4e00\u79cd\u6570\u5b66\u8868\u8fbe\u3002<\/span><\/p>\n


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\t\u56fe\u6a21\u578b\u7684\u4e00\u4e2a\u5de8\u5927\u4f18\u52bf\u5728\u4e8e\u76f4\u89c2\u5730\u8868\u793a\u53d8\u91cf\u7684\u56e0\u679c\u5173\u7cfb\u3002<\/span>\u96c6\u667a\u201c\u56e0\u679c\u63a8\u65ad\u201d\u7cfb\u5217\u6587\u7ae0\u91cc\u7684\u7b2c\u4e00\u8bb2<\/span><\/a>\u6709\u8bb2\u5230\uff0c\u6709\u5411\u56fe\u4e2d\u7684\u8def\u5f84\uff0c\u6709\u4e14\u4ec5\u6709\u4e09\u79cd\u57fa\u7840\u7ed3\u6784\uff1a\u5373\u94fe\u63a5\u5408\u3001\u53c9\u63a5\u5408\u3001\u5bf9\u649e\u63a5\u5408\uff0c\u5904\u4e8e\u7ed3\u70b9\u7684\u53d8\u91cf\u5206\u522b\u79f0\u4e3a\u4e2d\u4ecb\u53d8\u91cf\u3001\u6df7\u6742\u56e0\u5b50\u3001\u5bf9\u649e\u56e0\u5b50\u3002<\/span><\/p>\n


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\u5728\u6b64\u57fa\u7840\u4e0a\uff0c\u6709\u4e00\u4e9b\u6280\u5de7\u5df2\u7ecf\u88ab\u603b\u7ed3\u51fa\u6765\uff0c\u5e2e\u52a9\u5927\u5bb6\u5224\u65ad\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u6240\u6709\u8def\u5f84\u4e0a\u7684\u56e0\u679c\u4fe1\u606f\u4f20\u9012\u72b6\u6001\u3002\u6bd4\u5982\u8bf4\uff0c\u5728\u672c\u6587\u7684\u4f8b\u5b50\u4e2d\uff0c\u201c\u6559\u80b2\u6c34\u5e73\u201d\u540c\u65f6\u662f\u81ea\u53d8\u91cf\u548c\u56e0\u53d8\u91cf\u7684\u7236\u8f88\uff0c\u5373\u201c\u6559\u80b2\u6c34\u5e73\u201d\u540c\u65f6\u662f\u201c\u526f\u4e1a\u6295\u5165\u201d\u548c\u201c\u4e3b\u4e1a\u6536\u5165\u201d\u7684\u4e00\u4e2a\u539f\u56e0\u3002<\/span><\/p>\n


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<\/p>\n

<\/p>\n


<\/p>\n

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<\/span><\/p>\n

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<\/p>\n

<\/p>\n


<\/p>\n

\u7136\u800c\uff0c\u540e\u95e8\u6cd5\u5219\u7684\u4e00\u4e2a\u5c40\u9650\u6027\u5728\u4e8e\uff0c\u53ef\u80fd\u9020\u6210\u540e\u95e8\u7684\u53d8\u91cf\u5fc5\u987b\u80fd\u591f\u88ab\u89c2\u6d4b\u5230\u3002\u5982\u679c\u6709\u9057\u6f0f\u7684\u53d8\u91cf<\/span>\uff08omitted variable\uff09<\/span>\uff0c\u4e5f\u5c06\u4f1a\u5bf9\u56e0\u679c\u6548\u5e94\u4f30\u8ba1\u9020\u6210\u504f\u5dee\u3002\u4f8b\u5982\u4e0b\u56fe\u4e2d\uff0c\u6211\u4eec\u8981\u4f30\u8ba1X\u5bf9Y\u7684\u56e0\u679c\u6548\u5e94\uff0c\u4f46\u662f\u6211\u4eec\u77e5\u9053\u6709\u4e00\u4e2a\u53d8\u91cfU\uff0c\u540c\u65f6\u5f71\u54cdX\u548cY\uff0c\u4f46\u662f\u65e0\u6cd5\u88ab\u6d4b\u91cf\u5230<\/span>\uff08\u6bd4\u5982\u8bf4\u5927\u8111\u67d0\u533a\u57df\u7684\u6d3b\u52a8\u5f71\u54cd\u60c5\u7eea\u548c\u884c\u4e3a\uff0c\u4f46\u662f\u76ee\u524d\u6280\u672f\u624b\u6bb5\u8ba9\u6211\u4eec\u65e0\u6cd5\u7cbe\u51c6\u6d4b\u91cf\u5230\u8be5\u533a\u57df\u7684\u795e\u7ecf\u6d3b\u52a8\uff09<\/span>\uff0c\u6b64\u65f6\uff0c\u94fe\u7ed3\u5408\u4e3a\u6211\u4eec\u63d0\u4f9b\u4e86\u4e24\u79cd\u53ef\u80fd\u7684\u65b9\u6848\uff1a<\/span><\/p>\n


<\/span><\/p>\n

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<\/p>\n


<\/p>\n

\u7b2c\u4e8c\u79cd\u65b9\u6cd5\uff0c\u5de7\u5999\u7684\u5229\u7528\u7b2c\u4e09\u4e2a\u53d8\u91cf\uff0c\u521b\u9020\u4e00\u4e2a\u94fe\u7ed3\u5408\u3002\u5373\u627e\u5230\u4e00\u4e2a\u53d8\u91cfZ\uff0c\u4f7f\u5176\u53ea\u5f71\u54cdX\uff0c\u5e76\u4e14\u4e0d\u76f4\u63a5\u5f71\u54cdY\uff0c\u8fd9\u6837\u5c31\u5f62\u6210\u4e86Z->X->Y\u7684\u94fe\u7ed3\u5408\u3002\u793e\u4f1a\u79d1\u5b66\u6587\u732e\u4e2d\uff0c\u62bd\u7b7e\u662f\u4e00\u4e2a\u975e\u5e38\u597d\u7684\u5de5\u5177\u53d8\u91cf\uff0c\u5982\u8457\u540d\u7684Angrist  (1990) \u4e00\u6587\u4e2d\u7814\u7a76\u53c2\u52a0\u8d8a\u6218\u5bf9\u6218\u540e\u6536\u5165\u7684\u5f71\u54cd\uff0c\u5c31\u662f\u7528\u4e86\u5f81\u5175\u65f6\u7684\u62bd\u7b7e\u4f5c\u4e3a\u5de5\u5177\u53d8\u91cf\uff0c\u62bd\u7b7e\uff08Z\uff09\u53ea\u662f\u4e3a\u4e86\u9009\u51fa\u53c2\u6218\u7684\u58eb\u5175\uff0c\u4e0e\u53c2\u6218\uff08X\uff09\u6709\u5173\uff0c\u4f46\u4e0e\u5176\u4ed6\u7684\u4e8b\u60c5<\/span>\uff08\u6218\u540e\u6536\u5165\uff0cY\uff09<\/span>\u65e0\u5173\u3002\u4e5f\u5c31\u662f\u8bf4\uff0c\u62bd\u7b7e\u6709\u4e14\u53ea\u6709\u901a\u8fc7\u53c2\u52a0\u8d8a\u6218\u8fd9\u4e00\u6761\u8def\u5f84\u5f71\u54cd\u6218\u540e\u6536\u5165\u3002<\/span><\/p>\n


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<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

3. do-calculus<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


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\u5bf9\u7b2c\u4e00\u4e2a\u95ee\u9898\u7684\u56de\u7b54\uff0c\u7b54\u6848\u662f\u201c\u662f\u7684\uff01\u201d do-calculus\u53ef\u4ee5\u5b9e\u73b0\u3002\u51c6\u786e\u7684\u6765\u8bf4\uff0cPearl\u7684 do-calculus \u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u63a8\u65ad\u4efb\u4f55\u53ef\u88ab\u8bc6\u522b<\/span>\uff08identifiable\uff09<\/span>\u7684\u56e0\u679c\u5173\u7cfb<\/span>\uff08\u56e0\u4e3a\u4e0d\u662f\u6240\u6709\u7684causal quantities \u90fd\u53ef\u88ab\u8bc6\u522b\uff09<\/span>\u3002\u4e8b\u5b9e\u4e0a\uff0cPearl\u63d0\u51fa\u4e86do- calculus\u7684\u4e09\u6761\u89c4\u5219\uff0c\u6240\u6709\u53ef\u88ab\u8bc6\u522b\u7684\u56e0\u679c\u5173\u7cfb\u90fd\u53ef\u4ee5\u901a\u8fc7\u8fd9\u4e09\u6761\u89c4\u5219\u88ab\u8bc6\u522b\u3002\u8fd9\u4e09\u6761\u89c4\u5219\u7684\u524d\u4e24\u6761\uff0c\u5206\u522b\u662f\u5bf9\u524d\u95e8\u6cd5\u5219\u548c\u540e\u95e8\u6cd5\u5219\u7684\u63a8\u5e7f<\/span>\uff08generalization\uff09<\/span>\uff0c\u6362\u8a00\u4e4b\uff0c\u524d\u95e8\u6cd5\u5219\u548c\u540e\u95e8\u6cd5\u5219\u5206\u522b\u662f\u524d\u4e24\u6761\u89c4\u5219\u7684\u7279\u6b8a\u3001\u7b80\u5316\u60c5\u51b5\uff1b\u6b64\u5916\uff0c\u7531\u4e8e\u8fd9\u4e09\u6761\u89c4\u5219\u7684\u53ef\u7f16\u7a0b\u6027\u3001\u7b80\u6d01\u6027\uff0c\u4e0e\u624b\u52a8\u8dd1\u6a21\u578b\u3001\u6d4b\u8bd5\u76f8\u6bd4\uff0cdo-calculus\u662f\u4e00\u5957\u53ef\u4ee5\u81ea\u52a8\u5316\u8fdb\u884c\u56e0\u679c\u63a8\u7406\u7684\u65b9\u6cd5\u548c\u4f53\u7cfb\u3002\u4ece\u4ee5\u4e0a\u4e24\u70b9\u53ef\u4ee5\u770b\u51fado- calculus\u5728\u56e0\u679c\u63a8\u65ad\u7684\u5927\u9886\u57df\u4e2d\u5177\u6709\u72ec\u7279\u4f18\u52bf\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u9996\u5148\u6765\u770b\u4e00\u4e0b\u4ec0\u4e48\u662fdo\u7b97\u5b50\uff0c\u7136\u540e\u6765\u5177\u4f53\u770bdo- calculus\u7684\u4e09\u6761\u89c4\u5219\u3002<\/span><\/p>\n


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\u6362\u53e5\u8bdd\u8bf4\uff0c\u540c\u201c\u6f5c\u5728\u7ed3\u679c\u201d\u6846\u67b6\u4e00\u6837\uff0cdo- calculus\u4e5f\u6709\u7c7b\u4f3c\u7684\u8bc6\u522b-\u4f30\u8ba1\u6d41\u7a0b\uff0c\u5982\u4e0b\u56fe\u6240\u793a\uff1a\u9996\u5148\uff0c\u4ece\u4e25\u683c\u7684\u3001\u7406\u60f3\u5f97\u5b9e\u9a8c\u6761\u4ef6\u51fa\u53d1\uff0c\u5199\u51fa\u5982\u679c\u8981\u65e0\u504f\u4f30\u8ba1\u67d0\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u9700\u8981\u6ee1\u8db3\u4f55\u79cd\u5b9e\u9a8c\u6761\u4ef6\uff0c\u5373Causal Estimand P(Y\u4e28do<\/span>(T=t), X=x) \u3002\u7136\u540e\uff0c\u901a\u8fc7Pearl\u7684\u8bc1\u660e\uff0c\u4ed6\u53d1\u73b0\uff0c\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u901a\u8fc7\u5e72\u9884\u624d\u80fd\u505a\u5230\u7684\u5b9e\u9a8c\u6761\u4ef6\uff0c\u53ef\u4ee5\u8f6c\u5316\u4e3a\u53ea\u7528\u89c2\u6d4b\u6570\u636e\u5c31\u80fd\u6c42\u89e3\u3002\u4e5f\u5c31\u662f\u8bf4\uff0c\u8fd9\u4e9b\u60c5\u51b5\u4e0b\uff0c\u4e00\u4e2aCausual  Estimand<\/span>\uff08intervening\uff09<\/span>\u7684\u95ee\u9898\uff0c\u53ef\u4ee5\u8f6c\u5316\u4e3a\u4e00\u4e2aStatistical Estimand<\/span>\uff08conditioning\uff09<\/span>\u7684\u95ee\u9898\u6765\u6c42\u89e3\uff0c\u4f46\u8fd9\u4e2a\u8fc7\u7a0b\u9700\u8981\u6709\u5bf9\u4e8eCausal  model\u7684\u5047\u8bbe\uff0c\u4e5f\u5c31\u662f\u4e0a\u9762\u6240\u8bb2\u7684\u56e0\u679c\u56fe\uff0c\u5047\u8bbe\u597d\u6240\u6709\u7684\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff1b\u6700\u540e\uff0c\u53ea\u9700\u8981\u5c06\u89c2\u6d4b\u7684\u6570\u636e\u4ee3\u5165\uff0c\u5373\u53ef\u5bf9\u56e0\u679c\u6548\u5e94\u8fdb\u884c\u4f30\u8ba1\u3002<\/span><\/p>\n


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\u7b80\u5355\u6765\u8bf4\uff0cdo- calculus\u7684\u8fc7\u7a0b\u5c31\u662fCausal estimand\u4e2d\u7684\u6240\u6709\u5e26do\u7684\u3001\u4e0d\u505a\u5b9e\u9a8c\u4e0d\u53ef\u77e5\u7684\u9879\uff0c\u8f6c\u5316\u4e3aStatistical estimand\u4e2d\u4e0d\u5e26do\u7684\uff0c\u76f4\u63a5\u80fd\u4ece\u89c2\u6d4b\u6570\u636e\u4e2d\u83b7\u5f97\u7684\u9879\u3002\u5177\u4f53\u600e\u4e48\u8f6c\u5316\u5462\uff0c\u8981\u6839\u636edo- calculus\u7684\u4e09\u79cd\u89c4\u5219\uff1a<\/span><\/p>\n


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\u7b2c\u4e00\u6761\u89c4\u5219\uff1a\u662f\u5426\u5b58\u5728\u53ef\u5ffd\u7565\u7684\u53d8\u91cfZ\uff1f<\/span><\/p>\n


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\u7b2c\u4e8c\u6761\u89c4\u5219\uff1aAction\/Observation exchange (the back-door criterion)<\/span><\/p>\n


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\u7b2c\u4e09\u6761\u89c4\u5219\uff1a<\/span><\/p>\n


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\u7279\u4f8b\uff1a<\/span><\/p>\n


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\u6211\u4eec\u7684Causal estimand\u662f\uff1a<\/span><\/p>\n


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\u9996\u5148\u6211\u4eec\u89c2\u5bdf\u662f\u5426\u6709\u4efb\u4f55\u53ef\u4ee5\u5ffd\u7565\u7684\u53d8\u91cf<\/span>\uff08\u6bd4\u5982d- separate\u4e2d\u7684\u5bf9\u649e\u7ed3\u6784\uff09<\/span>\uff0c\u7136\u540e\u53d1\u73b0\u6ca1\u6709\uff0c\u6240\u4ee5\u89c4\u52191\u65e0\u6cd5\u4f7f\u7528\u3002\u6240\u4ee5\u6211\u4eec\u53ea\u80fd\u7ed3\u5408\u89c4\u52192\u548c3\u8fdb\u884c\u9010\u6b65\u63a8\u5bfc\uff0c\u8fc7\u7a0b\u5982\u4e0b\uff1a<\/span><\/p>\n


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\u6700\u540e\uff0c\u628a\u4e24\u8fb9\u7684\u7ed3\u679c\u63a5\u5408\u5728\u4e00\u8d77\uff0c\u53ef\u4ee5\u5f97\u5230Statistical Estimand\uff0c\u4e4b\u540e\u53ea\u9700\u8981\u76f4\u63a5\u5e26\u5165\u6570\u636e\u6c42\u89e3\u5373\u53ef\u3002<\/span><\/p>\n


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\u672c\u6587\u4e3b\u8981\u4e32\u8bb2\u4e86Pearl\u56e0\u679c\u8bc6\u522b\u6846\u67b6\u7684\u57fa\u7840\u77e5\u8bc6\uff0c\u5305\u62ec\u56fe\u6a21\u578b\u3001\u7ed3\u6784\u56e0\u679c\u6a21\u578b\u7684\u8303\u5f0f\uff0c\u4e09\u79cd\u8bc6\u522b\u7b56\u7565\uff0c\u4ee5\u53ca\u5982\u4f55\u8fd0\u7528do-calculus\u7684\u4e09\u79cd\u89c4\u5219\u6765\u8fdb\u884c\u56e0\u679c\u8bc6\u522b\u3002\u90a3\u662f\u5426\u5b58\u5728\u53ef\u88ab\u8bc6\u522b\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u4f46\u662f\u4e0d\u80fd\u901a\u8fc7do-calculus\u7684\u4ee5\u4e0a\u4e09\u6761\u89c4\u5219\u6765\u8bc6\u522b\u5462\uff1f\u5e78\u8fd0\u7684\u662f\uff0c do- calculus\u5df2\u7ecf\u88ab\u8bc1\u660e\u662f\u5b8c\u6574\u8986\u76d6\u4e86\u6240\u6709\u53ef\u8bc6\u522b\u56e0\u679c\u5173\u7cfb\u7684\u65b9\u6cd5<\/span>\uff08Shpister and Pearl 2006; Huang and Valtorta 2006\uff09<\/span>\uff0c\u5373\u4efb\u4f55\u53ef\u8bc6\u522b\u7684\u56e0\u679c\u5173\u7cfb\u90fd\u53ef\u4ee5\u901a\u8fc7do- calculus\u7684\u4e09\u79cd\u89c4\u5219\u6765\u8bc6\u522b\u3002<\/span><\/p>\n


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\u53c2\u8003\u6587\u732e\uff1a<\/span><\/strong><\/span><\/p>\n

Angrist, J. D. (1990). Lifetime earnings and the Vietnam era draft lottery: evidence from social security administrative records. The American Economic Review, 313-336.<\/span><\/p>\n

Huang, Y., & Valtorta, M. (2012). Pearl’s calculus of intervention is complete. arXiv preprint arXiv:1206.6831.<\/span><\/p>\n

Neal,B. (2020). Introduction to Causal Inference from a Machine Learning Perspective. https:\/\/www.bradyneal.com\/Introduction_to_Causal_Inference-Aug28_2020-Neal.pdf<\/span><\/p>\n

Pearl, J. (2019). The Seven Tools of Causal Inference with Reflections on Machine Learning, Communications of ACM, 62(3): 54-60, March 2019<\/span><\/p>\n

Shpitser, I., & Pearl, J. (2012). Identification of conditional interventional distributions. arXiv preprint arXiv:1206.6876.<\/span><\/p>\n

\u674e\u5949\u6cbb. (2020) \u56e0\u679c\u9636\u68af\u4e0eDo-\u6f14\u7b97\uff1a\u600e\u6837\u5b8c\u7f8e\u5730\u8bc1\u660e\u5438\u70df\u81f4\u764c\uff1f<\/span>https:\/\/mp.weixin.qq.com\/s\/SLBXgf8rkJaQwVzZhD_yAQ<\/span><\/a><\/p>\n


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\u56e0\u679c\u63a8\u65ad\u4e0e\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u7ed3\u5408\u5df2\u7ecf\u5438\u5f15\u4e86\u8d8a\u6765\u8d8a\u591a\u6765\u81ea\u5b66\u754c\u4e1a\u754c\u7684\u5173\u6ce8\uff0c\u4e3a\u6df1\u5165\u63a2\u8ba8\u3001\u666e\u53ca\u63a8\u5e7f\u56e0\u679c\u79d1\u5b66\u8bae\u9898\uff0c\u667a\u6e90\u793e\u533a\u643a\u624b\u96c6\u667a\u4ff1\u4e50\u90e8\u5c06\u4e3e\u529e\u7b2c\u4e8c\u5b63\u300c<\/span>\u56e0\u679c\u79d1\u5b66\u4e0eCausalAI\u8bfb\u4e66\u4f1a<\/a><\/span>\u300d\u3002\u672c\u671f\u8bfb\u4e66\u4f1a\u7740\u529b\u4e8e\u5b9e\u64cd\u6027\u3001\u57fa\u7840\u6027\uff0c\u5c06\u5e26\u9886\u5927\u5bb6\u7cbe\u8bfb\u56e0\u679c\u79d1\u5b66\u65b9\u5411\u4e24\u672c\u975e\u5e38\u53d7\u5e7f\u6cdb\u8ba4\u53ef\u7684\u5165\u95e8\u6559\u6750\u3002<\/span><\/section>\n

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1. Pearl, Judea, Madelyn Glymour, and Nicholas P. Jewell. Causal inference in statistics: A primer. John Wiley & Sons, 2016.<\/span>\uff08\u672c\u4e66\u4e2d\u8bd1\u7248\u300a\u7edf\u8ba1\u56e0\u679c\u63a8\u7406\u5165\u95e8\uff08\u7ffb\u8bd1\u7248\uff09\u300b\u5df2\u7531\u9ad8\u7b49\u6559\u80b2\u51fa\u7248\u793e\u51fa\u7248\uff09<\/span><\/section>\n

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2. Peters, Jonas, Dominik Janzing, and Bernhard Sch\u00f6lkopf. Elements of causal inference: foundations and learning algorithms. The MIT Press, 2017.<\/span><\/section>\n

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