Statistics How To

Genetic Matching: Simple Definition

Share on

Propensity Score Matching >

Genetic matching is an algorithm that iteratively checks propensity scores. It improves them using a combination of propensity score matching and Mahalanobis distance matching (Diamond & Sekhon, 2012).

The jury is out on whether genetic matching is a “better” method than any of the other matching techniques. Genetic matching may theoretically be a better choice if standard methods like full matching or nearest-neighbor greedy matching don’t sufficiently reduce imbalance (Holmes, 2013). Although some authors report good results, others (Holmes, 2013; Colson et al., 2016) either didn’t find any significant difference or reported that greedy matching was a lower performing method or equaled other matching methods.

Colson, K., Rudolph, K., Zimmerman, S. et al. Optimizing matching and analysis combinations for estimating causal effects. Sci Rep 6, 23222 (2016).
Diamond, A. & Sekhon, J. (2013). Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies. The Review of Economics and Statistics. July 2013, Vol. 95, No. 3, Pages: 932-945.
Holmes, W. (2013). Using Propensity Scores in Quasi-Experimental Designs. SAGE Publications.

Stephanie Glen. "Genetic Matching: Simple Definition" From Elementary Statistics for the rest of us!

Need help with a homework or test question? With Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. Your first 30 minutes with a Chegg tutor is free!

Comments? Need to post a correction? Please post a comment on our Facebook page.

Leave a Reply