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Comparison of Methods for Estimating Longitudinal Indirect Effects


Abstract Mediation analysis is used to investigate how an independent variable, X, is related to an outcome variable, Y, through a mediator variable, M (MacKinnon, 2008). If X represents a randomized intervention it is difficult to make a cause and effect inference regarding indirect effects without making no unmeasured confounding assumptions using the potential outcomes framework (Holland, 1988; MacKinnon, 2008; Robins & Greenland, 1992; VanderWeele, 2015), using longitudinal data to determine the temporal order of M and Y (MacKinnon, 2008), or both. The goals of this dissertation were to (1) define all indirect and direct effects in a three-wave longitudinal mediation model using the causal mediation formula (Pearl, 2012), (2) analytically co... (more)
Created Date 2018
Contributor Valente, Matthew John (Author) / MacKinnon, David P (Advisor) / West, Stephen G (Committee member) / Grimm, Keving (Committee member) / Chassin, Laurie (Committee member) / Arizona State University (Publisher)
Subject Statistics / Psychology / Causal inference / IPW / Longitudinal / Mediation / Sequential G-estimation
Type Doctoral Dissertation
Extent 183 pages
Language English
Copyright
Note Doctoral Dissertation Psychology 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis