| Sun | Mon | Tue | Wed | Thu | Fri | Sat |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | ||||
| 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| 11 | 12 | 13 | 14 | 15 | 16 | 17 |
| 18 | 19 | 20 | 21 | 22 | 23 | 24 |
| 25 | 26 | 27 | 28 | 29 | 30 |
« June 28, 2006 | Main | July 1, 2006 »
30 June 2006
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.