This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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402
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract - #307104 |
Title:
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Near/Far Matching: Building a Stronger Instrument
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Author(s):
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Mike Baiocchi*+ and Dylan Small and Scott Lorch and Paul Rosenbaum
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Companies:
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University of Pennsylvania and University of Pennsylvania and Children's Hospital of Philadelphia and University of Pennsylvania
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Address:
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3730 Walnut Street, Philadelphia, PA, 19104,
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Keywords:
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Causal inference ;
instrumental variables ;
strength of instrument ;
matching ;
binary outcomes
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Abstract:
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Instrumental variables (IV) is a framework for making causal inferences about the effect of a treatment based on an observational study in which there are unmeasured confounding variables. In many policy settings the objective is to estimate the effect of a treatment on a binary outcome. We develop a nonparametric matching technique - "near/far matching" - which is capable of estimating population level treatment effects when the outcome is binary. We provide a test statistic, with standard errors, and a method for sensitivity analysis. Many researchers assume the strength of a particular instrument is fixed. It is not. A novel feature of our method is that it allows us to manipulate the strength of a particular instrument. We illustrate our method using a study of neonatal intensive care units (NICUs) treatment effect on premature babies (preemies) born in Pennsylvania.
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