Sharp bounds on sufficient-cause interactions under the assumption of no redundancy

Abstract Background Sufficient-cause interaction is a type of interaction that has received much attention recently. The sufficient component cause model on which the sufficient-cause interaction is based is however a non-identifiable model. Estimating the interaction parameters from the model is ma...

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Main Author: Wen-Chung Lee
Format: Article
Language:English
Published: BMC 2017-04-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12874-017-0348-y
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author Wen-Chung Lee
author_facet Wen-Chung Lee
author_sort Wen-Chung Lee
collection DOAJ
description Abstract Background Sufficient-cause interaction is a type of interaction that has received much attention recently. The sufficient component cause model on which the sufficient-cause interaction is based is however a non-identifiable model. Estimating the interaction parameters from the model is mathematically impossible. Methods In this paper, I derive bounding formulae for sufficient-cause interactions under the assumption of no redundancy. Results Two real data sets are used to demonstrate the method (R codes provided). The proposed bounds are sharp and sharper than previous bounds. Conclusions Sufficient-cause interactions can be quantified by setting bounds on them.
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spelling doaj.art-b0e411a1e381418f8b92002a1c4a83da2022-12-21T20:10:57ZengBMCBMC Medical Research Methodology1471-22882017-04-011711610.1186/s12874-017-0348-ySharp bounds on sufficient-cause interactions under the assumption of no redundancyWen-Chung Lee0Research Center for Genes, Environment and Human Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan UniversityAbstract Background Sufficient-cause interaction is a type of interaction that has received much attention recently. The sufficient component cause model on which the sufficient-cause interaction is based is however a non-identifiable model. Estimating the interaction parameters from the model is mathematically impossible. Methods In this paper, I derive bounding formulae for sufficient-cause interactions under the assumption of no redundancy. Results Two real data sets are used to demonstrate the method (R codes provided). The proposed bounds are sharp and sharper than previous bounds. Conclusions Sufficient-cause interactions can be quantified by setting bounds on them.http://link.springer.com/article/10.1186/s12874-017-0348-ySufficient component cause modelEpidemiologic methodsCausal inferenceInteractionIdentifiability
spellingShingle Wen-Chung Lee
Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
BMC Medical Research Methodology
Sufficient component cause model
Epidemiologic methods
Causal inference
Interaction
Identifiability
title Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
title_full Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
title_fullStr Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
title_full_unstemmed Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
title_short Sharp bounds on sufficient-cause interactions under the assumption of no redundancy
title_sort sharp bounds on sufficient cause interactions under the assumption of no redundancy
topic Sufficient component cause model
Epidemiologic methods
Causal inference
Interaction
Identifiability
url http://link.springer.com/article/10.1186/s12874-017-0348-y
work_keys_str_mv AT wenchunglee sharpboundsonsufficientcauseinteractionsundertheassumptionofnoredundancy