Title:      Identification, Inference, and Sensitivity Analysis
for Causal Mediation Effects

Authors:    Kosuke Imai, Luke Keele, Teppei Yamamoto

Entrydate:  2009-07-20 23:13:22

Keywords:   causal inference, causal mediation analysis, direct
and indirect eects, linear structural equation models,
sequential ignorability, unmeasured confounders

Abstract:   Causal mediation analysis is routinely conducted by
applied researchers in a variety of disciplines including
epidemiology, political science, psychology, and sociology. The
goal of such an analysis is to investigate alternative causal
mechanisms by examining the roles of intermediate variables that
lie in the causal path between the treatment and outcome
variables. In this paper, we first prove that under a particular
version of sequential ignorability assumption, the average causal
mediation effect (ACME) is nonparametrically identified. We
compare our identifying assumption with those proposed in the
literature. Some practical implications of our identification
result are also discussed. In particular, the popular estimator
based on the linear structural equation model (LSEM) can be
interpreted as an ACME estimator if the linearity and
no-interaction assumptions are satisfied in addition to the
proposed assumption. We show that this assumption can easily be
relaxed within the framework of LSEM. Second, we consider a
simple nonparametric estimator of the ACME in order to relax
distributional and functional form assumptions. We also discuss
a more general nonparametric approach. Third, we propose a new
sensitivity analysis that can be easily implemented by applied
researchers within the standard LSEM framework. Like the
existing identifying assumptions, the proposed assumption may be
too strong in many applied settings. Thus, sensitivity analysis
is essential in order to examine the robustness of empirical
findings to the possible existence of an unmeasured confounder.
Finally, we apply the proposed methods to a randomized
experiment from political psychology.

http://polmeth.wustl.edu/retrieve.php?id=920

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