Accession Number:

ADA621962

Title:

Generalizing Experimental Findings

Descriptive Note:

Technical rept.

Corporate Author:

CALIFORNIA UNIV LOS ANGELES DEPT OF COMPUTER SCIENCE

Personal Author(s):

Report Date:

2015-06-01

Pagination or Media Count:

12.0

Abstract:

This note examines one of the most crucial questions in causal inference How generalizable are randomized clinical trials The question has received a formal treatment recently, using a non-parametric setting which has led to a simple and general solution. I will describe this solution and several of its ramifications, and compare it to the way researchers have attempted to tackle the problem using the language of ignorability. We will see that ignorability-type assumptions need to be enriched with structural assumptions in order to capture the full spectrum of conditions that permit generalizations, and in order to judge their plausibility in specific applications.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE