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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/120186
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dc.contributor.authorMoreno-Betancur, M.-
dc.contributor.authorKoplin, J.-
dc.contributor.authorPonsonby, A.-L.-
dc.contributor.authorLynch, J.-
dc.contributor.authorCarlin, J.-
dc.date.issued2018-
dc.identifier.citationInternational Journal of Epidemiology, 2018; 47(1):217-225-
dc.identifier.issn0300-5771-
dc.identifier.issn1464-3685-
dc.identifier.urihttp://hdl.handle.net/2440/120186-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityMargarita Moreno-Betancur, Jennifer J Koplin, Anne-Louise Ponsonby, John Lynch, and John B Carlin-
dc.language.isoen-
dc.publisherOxford University Press-
dc.rights© The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association-
dc.source.urihttp://dx.doi.org/10.1093/ije/dyx194-
dc.subjectPopulation comparison; disease occurrence; risk factor distribution; contribution of risk factors; causal inference; standardization; g-computation; doubly robust; inverse probability weighting; average treatment effect on the treated-
dc.titleMeasuring the impact of differences in risk factor distributions on cross-population differences in disease occurrence: a causal approach-
dc.typeJournal article-
dc.identifier.doi10.1093/ije/dyx194-
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1035261-
pubs.publication-statusPublished-
dc.identifier.orcidLynch, J. [0000-0003-2781-7902]-
Appears in Collections:Aurora harvest 8
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