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.
Original language | English (US) |
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Pages (from-to) | 237-253 |
Number of pages | 17 |
Journal | Health Services and Outcomes Research Methodology |
Volume | 12 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2012 |
Externally published | Yes |
Keywords
- Binary outcomes
- Comparative effectiveness
- Instrumental variables
- Matching
- Medicare data
- Study design
ASJC Scopus subject areas
- Health Policy
- Public Health, Environmental and Occupational Health