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Uncovering causal mechanisms: Three ...

Park, Soojin.

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Uncovering causal mechanisms: Three extensions of causal mediation analysis.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Uncovering causal mechanisms: Three extensions of causal mediation analysis./
Author:	Park, Soojin.
Description:	140 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Contained By:	Dissertation Abstracts International77-10B(E).
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10126389
ISBN:	9781339844299

Uncovering causal mechanisms: Three extensions of causal mediation analysis.
Park, Soojin.

Uncovering causal mechanisms: Three extensions of causal mediation analysis. - 140 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2016.

Education researchers interested in the causal effects of interventions are often interested in also understanding causal mechanisms---i.e., why and how a treatment has an effect. Causal Mediation Analysis is a statistical framework that allows researchers to investigate why and how a treatment has its effect on an outcome. Current work on causal mediation analysis reveals several limitations: 1) recent papers are based predominantly within the frequentist framework while there have been few attempts to understand causal mediation analysis within the Bayesian framework, 2) most of the work has been discussed in the presence of perfect compliance to a treatment and with a single mediator---which is unlikely to reflect real-life applications, and 3) few studies exist on longitudinal causal mediation analysis with time-varying covariates. In response to these limitations, the aim of this dissertation is to develop three extensions of causal mediation analysis: 1) Bayesian Causal Mediation Analysis with a Group Randomized Design (Park and Kaplan, 2015), 2) Bayesian Causal Mediation Analysis with Multiple Mediations in the Presence of Treatment No-compliance, and 3) Causal Mediation Analysis under Longitudinal Settings. Possible ways to accommodate these limitations are discussed in the context of a real-life example. It concludes with discussions and future directions.

ISBN: 9781339844299Subjects--Topical Terms:

517247
Statistics.

Uncovering causal mechanisms: Three extensions of causal mediation analysis.
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245 1 0 $a Uncovering causal mechanisms: Three extensions of causal mediation analysis.
300 $a 140 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
500 $a Adviser: David Kaplan.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2016.
520 $a Education researchers interested in the causal effects of interventions are often interested in also understanding causal mechanisms---i.e., why and how a treatment has an effect. Causal Mediation Analysis is a statistical framework that allows researchers to investigate why and how a treatment has its effect on an outcome. Current work on causal mediation analysis reveals several limitations: 1) recent papers are based predominantly within the frequentist framework while there have been few attempts to understand causal mediation analysis within the Bayesian framework, 2) most of the work has been discussed in the presence of perfect compliance to a treatment and with a single mediator---which is unlikely to reflect real-life applications, and 3) few studies exist on longitudinal causal mediation analysis with time-varying covariates. In response to these limitations, the aim of this dissertation is to develop three extensions of causal mediation analysis: 1) Bayesian Causal Mediation Analysis with a Group Randomized Design (Park and Kaplan, 2015), 2) Bayesian Causal Mediation Analysis with Multiple Mediations in the Presence of Treatment No-compliance, and 3) Causal Mediation Analysis under Longitudinal Settings. Possible ways to accommodate these limitations are discussed in the context of a real-life example. It concludes with discussions and future directions.
590 $a School code: 0262.
650 4 $a Statistics. $3 517247
650 4 $a Educational evaluation. $3 526425
650 4 $a Quantitative psychology. $3 2144748
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710 2 $a The University of Wisconsin - Madison. $b Educational Psychology. $3 3170079
773 0 $t Dissertation Abstracts International $g 77-10B(E).
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10126389