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Causal effects in mediation analysiswith limited-dependent variables
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Mediation is used to separate direct and indirect effects of an exposure variable on anoutcome variable. In this thesis, a mediation model is extended to account for censoredmediator and outcome variable. The two-part framework is used to account for thecensoring. The counterfactual based causal effects of this model are derived. A MonteCarlo study is performed to evaluate the behaviour of the causal effects accounting forcensoring, together with a comparison with methods for estimating the causal effectswithout accounting for censoring. The results of the Monte Carlo study show that theeffects accounting for censoring have substantially smaller bias when censoring is present.The proposed effects also seem to have a low cost with unbiased estimates for samplesizes as small as 100 for the two-part mediator model. In the case of limited mediatorand outcome, sample sizes larger than 300 is required for reliable improvements. A smallsensitivity analysis stresses the need of further development of the two-part models.

Place, publisher, year, edition, pages
2016. , 87 p.
Keyword [en]
counterfactuals, two-part model, potential outcome
National Category
Probability Theory and Statistics
URN: urn:nbn:se:uu:diva-297041OAI: oai:DiVA.org:uu-297041DiVA: diva2:940585
Educational program
Master Programme in Statistics
Available from: 2016-06-27 Created: 2016-06-21 Last updated: 2016-06-27Bibliographically approved

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