I use Propensity score matching for two different kinds of treatment (dummy and continuous treatment), which I will use each treatment in separate regression. So I converted the continuous treatment (the board of director number) into the dummy, and used the Mahalanobis matching within propensity score calipers. However, I'm not sure how to support my argument, especially after reading the advantages and disadvantages of this method? (I use Rstudio) is this method is acceptable in business research?
Also, I'm not sure that other method methods like GPS will be the same effective as the Mahalanobis matching within propensity score calipers to achieve covariate balance for panel data?
Hello Randa,
Yes, with: (a) more variables; (b) continuous variables; and (c) a modest data set, getting good matches is very challenging. If your rationale was that converting from continuous to dichotomous made the matching easier or viable, given your sample size, then just be clear about that. If the reason was something else, then just explain that in your method section. The Mahalanobis distance could work as an indicator of proximity either way (continuous vs. dichotomous variable).
I am unable to offer an opinion as to which approach may be preferred among consumers or producers of business research. If you're considering submission of your project to some journal, perhaps you should have a look at what method similar studies have used within that journal.
Good luck with your work.
Hi Dr David
Thank you very much for your clear explanation, I attend to submit it to journal and I was searching for research that used a similar method and has converted a continuous variable into a dummy as u suggested
I hope to find one David Morse
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