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[journal article]

dc.contributor.authorHoffmann, Rasmusde
dc.contributor.authorDoblhammer, Gabrielede
dc.date.accessioned2021-05-19T10:02:50Z
dc.date.available2021-05-19T10:02:50Z
dc.date.issued2021de
dc.identifier.issn1869-8999de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/73127
dc.description.abstractWe aim to give an overview of the state of the art of causal analysis of demographic issues related to morbidity and mortality. We will systematically introduce strategies to identify causal mechanisms, which are inherently linked to panel data from observational surveys and population registers. We will focus on health and mortality, and on the issues of unobserved heterogeneity and reverse causation between health and (1) retirement, (2) socio-economic status, and (3) characteristics of partnership and fertility history. The boundaries between demographic research on mortality and morbidity and the neighbouring disciplines epidemiology, public health and economy are often blurred. We will highlight the specific contribution of demography by reviewing methods used in the demographic literature. We classify these methods according to important criteria, such as a design-based versus model-based approach and control for unobserved confounders. We present examples from the literature for each of the methods and discuss the assumptions and the advantages and disadvantages of the methods for the identification of causal effects in demographic morbidity and mortality research. The differentiation between methods that control for unobserved confounders and those that do not reveal a fundamental difference between (1) methods that try to emulate a randomised experiment and have higher internal validity and (2) methods that attempt to achieve conditional independence by including all relevant factors in the model. The latter usually have higher external validity and require more assumptions and prior knowledge of relevant factors and their relationships. It is impossible to provide a general definition of the sort of validity that is more important, as there is always a trade-off between generalising the results to the population of interest and avoiding biases in the estimation of causal effects in the sample. We hope that our review will aid researchers in identifying strategies to answer their specific research question.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.titleApproaches and Methods for Causal Analysis of Panel Data in the Area of Morbidity and Mortalityde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalComparative Population Studies - Zeitschrift für Bevölkerungswissenschaft
dc.source.volume46de
dc.publisher.countryDEU
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozPopulation Studies, Sociology of Populationen
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.classozBevölkerungde
dc.subject.thesozValiditätde
dc.subject.thesozGesundheitde
dc.subject.thesozKausalanalysede
dc.subject.thesozcausal analysisen
dc.subject.thesozmortalityen
dc.subject.thesozpanelen
dc.subject.thesozMethodede
dc.subject.thesozmethoden
dc.subject.thesozSterblichkeitde
dc.subject.thesozcausalityen
dc.subject.thesozPanelde
dc.subject.thesozMorbiditätde
dc.subject.thesozvalidityen
dc.subject.thesozmorbidityen
dc.subject.thesozhealthen
dc.subject.thesozKausalitätde
dc.rights.licenceCreative Commons - Namensnennung, Weitergabe unter gleichen Bedingungen 4.0de
dc.rights.licenceCreative Commons - Attribution-ShareAlike 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10045492
internal.identifier.thesoz10035491
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dc.type.stockarticlede
dc.type.documentjournal articleen
dc.type.documentZeitschriftenartikelde
dc.source.pageinfo69-96de
internal.identifier.classoz10303
internal.identifier.classoz10105
internal.identifier.journal60
internal.identifier.document32
internal.identifier.ddc300
dc.source.issuetopicIdentification of causal mechanisms in demographic research: the contribution of panel datade
dc.identifier.doihttps://doi.org/10.12765/CPoS-2021-03de
dc.description.pubstatusPublished Versionen
dc.description.pubstatusVeröffentlichungsversionde
internal.identifier.licence24
internal.identifier.pubstatus1
internal.identifier.review1
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse
ssoar.urn.registrationfalsede


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