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dc.contributor.authorPAKPAHAN, Eduwin
dc.contributor.authorKRÖGER, Hannes
dc.contributor.authorHOFFMANN, Rasmus
dc.date.accessioned2016-01-14T13:50:01Z
dc.date.available2016-01-14T13:50:01Z
dc.date.issued2017
dc.identifier.citationInternational journal of social research methodology, 2017, Vol. 20, No. 1, pp. 1-19en
dc.identifier.issn1464-5300
dc.identifier.issn1364-5579
dc.identifier.urihttps://hdl.handle.net/1814/38412
dc.descriptionFirst published online 13 October 2015.en
dc.description.abstractWe present three statistical methods for causal analysis in life course research that are able to take into account the order of events and their possible causal relationship: a cross-lagged model, a latent growth model (LGM), and a synthesis of the two, an autoregressive latent trajectories model (ALT). We apply them to a highly relevant causality question in life course and health inequality research: does socioeconomic status (SES) affect health (social causation) or does health affect SES (health selection)? Using retrospective survey data from SHARELIFE covering life courses from childhood to old age, the cross-lagged model suggests an equal importance of social causation and health selection; the LGM stresses the effect of education on health growth; whereas the ALT model confirms no causality. We discuss examples, present short and non-technical introduction of each method, and illustrate them by highlighting their relative strengths for causal life course analysis.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherTaylor & Francis (Routledge)en
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/313532
dc.relation.ispartofInternational journal of social research methodology
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleStatistical methods for causal analysis in life course research : an illustration of a cross-lagged structural equation model, a latent growth model, and an autoregressive latent trajectories modelen
dc.typeArticleen
dc.identifier.doi10.1080/13645579.2015.1091641
dc.identifier.volume20
dc.identifier.startpage1
dc.identifier.endpage19
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dc.identifier.issue1


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