Abstract Details
Activity Number:
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115
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 4, 2014 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #311763
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View Presentation
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Title:
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Instrumental Variable Approach for Mediation Analysis on Count and Zero-Inflated Count Data
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Author(s):
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Zijian Guo*+ and Jing Cheng and Dylan Small and Stuart Gansky
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Companies:
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Wharton School and University of California, San Francisco and University of Pennsylvania and University of California, San Francisco
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Keywords:
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Estimating Equations ;
Empirical Likelihood ;
Instrumental Variable ;
Count Outcome ;
Zero-inflated Outcome
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Abstract:
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Most existing approaches for mediation analysis are developed for continuous or binary mediators and/or outcomes. However, count or zero-infated count data is common in many studies. In this study, we develop causal methods based on instrumental variable approaches for mediation analysis for those data without the assumption of sequential ignorability when confounders invalidate the assumption. We propose estimating equations and solve the equations directly or use empirical likelihood to estimate the mediation eect consistently. Simulation studies show that our method works well. Our method is applied in a study of caries prevention to study the direct and mediation effects of intervention on count and zero-inflated count outcomes through oral health behaviors.
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