Propensity Scores: An Introduction and Experimental Test  

Oleh:

Luellen, Jason K. ; Shadish, William R. ; Clark, M. H.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Evaluation Review vol. 29 no. 6 (Dec. 2005), page 530-558.
Topik: propensity score; quasi-experiment; classification tree; bagging; ensemble methods
Fulltext: 530.pdf (164.0KB)

Isi artikel

Propensity score analysis is a relatively recent statistical innovation that is useful in the analysis of data from quasi-experiments. The goal of propensity score analysis is to balance two nonequivalent groups on observed covariates to get more accurate estimates of the effects of a treatment on which the two groups differ. This article presents a general introduction to propensity score analysis, provides an example using data from a quasi-experiment compared to a benchmark randomized experiment, offers practical advice about how to do such analyses, and discusses some limitations of the approach. It also presents the first detailed instructions to appear in the literature on how to use classification tree analysis and bagging for classification trees in the construction of propensity scores. The latter two examples serve as an introduction for researchers interested in computing propensity scores using more complex classification algorithms known as ensemble methods.

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