Volltext herunterladen
(externe Quelle)
Zitationshinweis
Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):
https://doi.org/10.12765/CPoS-2021-03
Export für Ihre Literaturverwaltung
Approaches and Methods for Causal Analysis of Panel Data in the Area of Morbidity and Mortality
[Zeitschriftenartikel]
Abstract We 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... mehr
We 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.... weniger
Thesaurusschlagwörter
Validität; Gesundheit; Kausalanalyse; Methode; Sterblichkeit; Panel; Morbidität; Kausalität
Klassifikation
Bevölkerung
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Sprache Dokument
Englisch
Publikationsjahr
2021
Seitenangabe
S. 69-96
Zeitschriftentitel
Comparative Population Studies - Zeitschrift für Bevölkerungswissenschaft, 46 (2021)
Heftthema
Identification of causal mechanisms in demographic research: the contribution of panel data
ISSN
1869-8999
Status
Veröffentlichungsversion; begutachtet (peer reviewed)
Lizenz
Creative Commons - Namensnennung, Weitergabe unter gleichen Bedingungen 4.0