Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies
Identifying causal mechanisms is a fundamental goal of social science. Researchers seek to study not only whether one variable affects another but also how such a causal relationship arises. Yet commonly used statistical methods for identifying causal mechanisms rely upon untestable assumptions and...
Main Authors: | Yamamoto, Teppei, Imai, Kosuke, Keele, Luke, Tingley, Dustin |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Political Science |
Format: | Article |
Language: | en_US |
Published: |
Cambridge University Press
2014
|
Online Access: | http://hdl.handle.net/1721.1/84065 https://orcid.org/0000-0002-8079-7675 |
Similar Items
-
Experimental designs for identifying causal mechanisms
by: Imai, Kosuke, et al.
Published: (2014) -
Commentary: Practical implications of theoretical results for causal mediation analysis
by: Imai, Kosuke, et al.
Published: (2015) -
mediation: R package for causal mediation analysis
by: Tingley, Dustin, et al.
Published: (2014) -
IDENTIFYING MECHANISMS BEHIND POLICY INTERVENTIONS VIA CAUSAL MEDIATION ANALYSIS
by: Keele, Luke, et al.
Published: (2015) -
Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments
by: Yamamoto, Teppei, et al.
Published: (2014)