Near/Far Matching: A Study Design Approach to Instrumental Variables

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Statistics Papers
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instrumental variables
matching
study design
binary outcomes
comparative effectiveness
medicare data
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Vital and Health Statistics
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Baiocchi, Mike
Small, Dylan S
Yang, Lin
Polsky, Daniel
Groeneveld, Peter W
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Abstract

Classic instrumental variable techniques involve the use of structural equation modeling or other forms of parameterized modeling. In this paper we use a nonparametric, matching-based instrumental variable methodology that is based on a study design approach. Similar to propensity score matching, though unlike classic instrumental variable approaches, near/far matching is capable of estimating causal effects when the outcome is not continuous. Unlike propensity score matching, though similar to instrumental variable techniques, near/far matching is also capable of estimating causal effects even when unmeasured covariates produce selection bias. We illustrate near/far matching by using Medicare data to compare the effectiveness of carotid arterial stents with cerebral protection versus carotid endarterectomy for the treatment of carotid stenosis.

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2012-12-01
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Health Services and Outcomes Research Methodology
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