JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home
My Program

Abstract Details

Activity Number: 392
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #304761
Title: Making Instrumental Variables Look More Like Experimental Design
Author(s): Mike Baiocchi*+ and Dylan Small and Daniel Polsky
Companies: Stanford University and The Wharton School and University of Pennsylvania
Address: Department of Statistics, Stanford, CA, , United States
Keywords: instrumental variables ; causal inference ; near/far matching ; study design ; propensity score ; matching
Abstract:

Instrumental variable (IV) techniques are typically conceptualized and implemented under a structural equation modelling framework(e.g., two stage least squares). This is not the only framework for IV. A study design approach to IV has been developed. This technique, called near/far matching, follows the logic of a randomized controlled trial to obtain causal estimates in an observational setting.

We will start by introducing near/far matching and discussing its connection to propensity score matching. We will then introduce a methodology for designing a strong study using near/far matching, both when you believe you have a valid instrument and when you suspect a violation of the IV assumptions.


The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program




2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.