{"id":206,"date":"2011-12-06T08:50:07","date_gmt":"2011-12-06T08:50:07","guid":{"rendered":"http:\/\/rulesofreason.wordpress.com\/?p=206"},"modified":"2011-12-06T08:50:07","modified_gmt":"2011-12-06T08:50:07","slug":"is-unit-homogeneity-a-sufficient-assumption-for-causal-inference","status":"publish","type":"post","link":"http:\/\/re-design.dimiter.eu\/?p=206","title":{"rendered":"Is unit homogeneity a sufficient assumption for causal inference?"},"content":{"rendered":"

Is unit homogeneity a sufficient<\/strong> condition (assumption) for causal inference from observational data?<\/p>\n

Re-reading King, Keohane and Verba’s bible on research design\u00a0<\/a>[lovingly known to all exposed\u00a0as KKV] I\u00a0think\u00a0they regard unit homogeneity and conditional independence as alternative<\/strong> assumptions for causal inference. For example: “we provide an overview here of what is required in terms of the two possible<\/strong> assumptions that enable us to get around the fundamental problem [of causal inference]” (p.91, emphasis mine). However,\u00a0I don’t see how unit homogeneity on its own can rule out endogeneity (establish the direction of causality). In my understanding, endogeneity is automatically\u00a0ruled out\u00a0with conditional independence, but not with unit homogeneity (“Two units are homogeneous when the expected values of the dependent variables from each unit are the same when our explanatory variables takes on a particular value<\/em>” [p.91]).<\/p>\n

Going back to Holland’s\u00a0seminal article<\/a> which provides the basis of KKV’s approach, we can confirm that unit homogeneity is listed as a sufficient<\/strong> condition for inference (p.948). But Holland divides variables into pre-exposure<\/strong> and post-exposure<\/strong>\u00a0before he even gets to discuss any of the additional assumptions, so reverse causality is ruled out altogether.\u00a0Hence, in Holland’s context unit homogeneity can indeed be regarded as sufficient, but in my\u00a0opinion\u00a0in KKV’s context\u00a0unit homogeneity needs to be coupled with some condition (temporal precedence for example) to ascertain the causal direction when making inferences from data.<\/p>\n

The point is minor but can create confusion when\u00a0presenting unit homogeneity and conditional independence side by side as alternative assumptions\u00a0for inference.<\/p>\n","protected":false},"excerpt":{"rendered":"

Is unit homogeneity a sufficient condition (assumption) for causal inference from observational data? Re-reading King, Keohane and Verba’s bible on research design\u00a0[lovingly known to all exposed\u00a0as KKV] I\u00a0think\u00a0they regard unit homogeneity and conditional independence as alternative assumptions for causal inference. For example: “we provide an overview here of what is required in terms of the two possible assumptions that enable us to get around the fundamental problem [of causal inference]” (p.91, emphasis mine). However,\u00a0I don’t see how unit homogeneity on its own can rule out endogeneity (establish the direction of causality). In my understanding, endogeneity is automatically\u00a0ruled out\u00a0with conditional independence, but not with unit homogeneity (“Two units are homogeneous when the expected values of the dependent variables from each unit are the same when our explanatory variables takes on a particular value” [p.91]). Going back to Holland’s\u00a0seminal article which provides the basis of KKV’s approach, we can confirm that unit homogeneity is listed as a sufficient condition for inference (p.948). But Holland divides variables into pre-exposure and post-exposure\u00a0before he even gets to discuss any of the additional assumptions, so reverse causality is ruled out altogether.\u00a0Hence, in Holland’s context unit homogeneity can indeed be regarded as sufficient, but in my\u00a0opinion\u00a0in KKV’s context\u00a0unit homogeneity needs to be coupled with some condition (temporal precedence for example) to ascertain the causal direction when making inferences from data. The point is minor but can create confusion when\u00a0presenting unit homogeneity and conditional independence side by side as alternative assumptions\u00a0for inference.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false},"categories":[8,33],"tags":[81,120,121,146,226,289,370,371,445,467,562,566,636,668],"jetpack_featured_media_url":"","jetpack_publicize_connections":[],"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p7g3hj-3k","jetpack-related-posts":[{"id":331,"url":"http:\/\/re-design.dimiter.eu\/?p=331","url_meta":{"origin":206,"position":0},"title":"Explanation and the quest for 'significant' relationships. Part I","date":"February 17, 2012","format":false,"excerpt":"The ultimate goal of social science is causal explanation*. 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Recently, COMPASSS\u2026","rel":"","context":"In "Causality"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":57,"url":"http:\/\/re-design.dimiter.eu\/?p=57","url_meta":{"origin":206,"position":4},"title":"Inspiring scientific concepts","date":"October 16, 2011","format":false,"excerpt":"EDGE asks 159 selected intellectuals What scientific concept would improve everybody's cognitive toolkit? You are welcome to read the individual contributions which range from a paragraph to a short essay here. Many of the entries are truly inspiring but I see little synergy of bringing 159 of them together. Like\u2026","rel":"","context":"In "Causality"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/img.youtube.com\/vi\/2kotK9FNEYU\/0.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":336,"url":"http:\/\/re-design.dimiter.eu\/?p=336","url_meta":{"origin":206,"position":5},"title":"Explanation and the quest for 'significant' relationships. 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