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By: Gary King - Re: The Balance Test Fallacy in Matching Methods for Causal Inference
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30 June 2006
The Balance Test Fallacy in Matching Methods for Causal Inference
We've talked a lot on this blog about evaluating the quality of matching solutions when applying these matching for preprocessing, and in some of these discussions I've previewed and referenced arguments from a paper I was working on with Kosuke Imai and Liz Stuart. We have finally finished the paper. For anyone interested, you can get a copy here. The abstract follows. Comments welcome!
Matching methods are widely used to adjust for nonrandom treatment assignment when making causal inferences. In numerous articles across a diverse variety of academic fields that use matching, researchers evaluate the success of the procedure by conducting hypothesis tests, most commonly the t-test for the mean difference of each of the observed covariates between the matched treated and control groups. We demonstrate that these hypothesis tests are fallacious and discuss better alternatives.
Posted by Gary King at June 30, 2006 7:47 AM
Comments
Hi Kosuke, Gary, and Liz, Wonderful paper. I particularly like the second argument (which shows how you can pass conventional balance tests by actually making balance worse :-). But could it be that there are a few lines of text missing on page 3 of the pdf. Best, Felix
Posted by: Felix Elwert at July 2, 2006 8:41 AM
Thanks Felix. It looks like the Figure caption is hard to distinguish from the text. We'll fix it and post a new version.
Gary
Posted by: Gary King ![[TypeKey Profile Page]](http://www.iq.harvard.edu/blog/sss/nav-commenters.gif)
at July 2, 2006 9:05 AM