2SLS Versus 2SRI: Appropriate Methods for Rare Outcomes and/or Rare Exposures

Simple item page
dc.contributor.authorBasu, Anirban
dc.contributor.authorCoe, Norma B
dc.contributor.authorChapman, Cole G
dc.date2023-05-17T22:51:44.000
dc.date.accessioned2023-05-22T23:51:23Z
dc.date.available2023-05-22T23:51:23Z
dc.date.issued2018-06-01
dc.date.submitted2019-10-07T10:30:57-07:00
dc.description.abstractThis study used Monte Carlo simulations to examine the ability of the two-stage least squares (2SLS) estimator and two-stage residual inclusion (2SRI) estimators with varying forms of residuals to estimate the local average and population average treatment effect parameters in models with binary outcome, endogenous binary treatment, and single binary instrument. The rarity of the outcome and the treatment was varied across simulation scenarios. Results showed that 2SLS generated consistent estimates of the local average treatment effects (LATE) and biased estimates of the average treatment effects (ATE) across all scenarios. 2SRI approaches, in general, produced biased estimates of both LATE and ATE under all scenarios. 2SRI using generalized residuals minimized the bias in ATE estimates. Use of 2SLS and 2SRI is illustrated in an empirical application estimating the effects of long-term care insurance on a variety of binary health care utilization outcomes among the near-elderly using the Health and Retirement Study.
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/40115
dc.legacy.articleid1008
dc.legacy.fields10.1002/hec.3647
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1008&context=mehp&unstamped=1
dc.rightsThis is the peer reviewed version of the following article: Basu, Anirban, Coe, Norma B., Chapman, Cole G.. (2018). 2SLS versus 2SRI: Appropriate methods for rare outcomes and/or rare exposures. Health Economics, 27(6), 937-955. DOI: 10.1002/hec.3647., which has been published in final form at https://doi.org/10.1002/hec.3647. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
dc.source.beginpage937
dc.source.endpage955
dc.source.issue2
dc.source.issue6
dc.source.journalDepartment of Medical Ethics and Health Policy
dc.source.journaltitleHealth Economics
dc.source.statuspublished
dc.source.volume27
dc.subject.otherAged
dc.subject.otherComputer Simulation
dc.subject.otherHumans
dc.subject.otherLong-Term Care
dc.subject.otherModels, Econometric
dc.subject.otherMonte Carlo Method
dc.subject.otherPatient Acceptance of Health Care
dc.subject.otherAged
dc.subject.otherComputer Simulation
dc.subject.otherHumans
dc.subject.otherLong-Term Care
dc.subject.otherModels
dc.subject.otherEconometric
dc.subject.otherMonte Carlo Method
dc.subject.otherPatient Acceptance of Health Care
dc.subject.otherMedicine and Health Sciences
dc.title2SLS Versus 2SRI: Appropriate Methods for Rare Outcomes and/or Rare Exposures
dc.typeArticle
digcom.contributor.authorBasu, Anirban
digcom.contributor.authorisAuthorOfPublication|email:nbcoe@pennmedicine.upenn.edu|institution:University of Pennsylvania|Coe, Norma B
digcom.contributor.authorChapman, Cole G
digcom.identifiermehp/2
digcom.identifier.contextkey15506408
digcom.identifier.submissionpathmehp/2
digcom.typearticle
dspace.entity.typePublication
relation.isAuthorOfPublication452b4a57-6747-4483-8846-1fadd0ea9a6c
relation.isAuthorOfPublication.latestForDiscovery452b4a57-6747-4483-8846-1fadd0ea9a6c
upenn.schoolDepartmentCenterDepartment of Medical Ethics and Health Policy
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
nihms_1017133.pdf
Size:
556.29 KB
Format:
Adobe Portable Document Format
Download
Collection
Articles