Rollmatch: An R package for rolling entry matching

2Citations
Citations of this article
267Readers
Mendeley users who have this article in their library.

Abstract

The gold standard of experimental research is the randomized control trial. However, interventions are often implemented without a randomized control group for practical or ethical reasons. Propensity score matching (PSM) is a popular method for minimizing the effects of a randomized experiment from observational data by matching members of a treatment group to similar candidates that did not receive the intervention. Traditional PSM is not designed for studies that enroll participants on a rolling basis and does not provide a solution for interventions in which the baseline and intervention period are undefined in the comparison group. Rolling Entry Matching (REM) is a new matching method that addresses both issues. REM selects comparison members who are similar to intervention members with respect to both static (e.g., race) and dynamic (e.g., health conditions) characteristics. This paper will discuss the key components of REM and introduce the rollmatch R package.

Cite

CITATION STYLE

APA

Jones, K., Chew, R., Witman, A., & Liu, Y. (2019). Rollmatch: An R package for rolling entry matching. R Journal, 11(2), 243–253. https://doi.org/10.32614/rj-2019-005

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free