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      Do We Necessarily Need Longitudinal Data to Infer Causal Relations?

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          Abstract

          A-t-on nécessairement besoin de données longitudinales pour inférer des relations causales ? Il est généralement admis que les causes précèdent leurs effets dans le temps. Cela justifie usuellement la préférence pour les études longitudinales par rapport aux études transversales, parce que les premières permettent la modèlisation du processus dynamique engendrant le résultat, tandis que les secondes ne le peuvent pas. Les partisans de l’approche longitudinale proposent deux justifications interdépendantes : (i) l’inférence causale nécessite le suivi des mêmes personnes au fil du temps, et (ii) aucune inférence causale ne peut être tirée de données transversales. Dans cet article, nous remettons en question ce point de vue et proposons des objections à ces deux arguments. Nous soutenons également que la possibilité d’établir des relations de cause à effet ne dépend pas tant de l’utilisation de données longitudinales ou transversales, mais plutôt de savoir si la stratégie de modélisation est d’ordre structurel ou non.

          Abstract

          It is generally admitted that causes precede their effects in time. This usually justifies the preference for longitudinal studies over cross-sectional ones, because the former allow the modelling of the dynamic process generating the outcome, while the latter cannot. Supporters of the longitudinal view make two interrelated claims: (i) causal inference requires following the same individuals over time, and (ii) no causal inference can be drawn from cross-sectional data. In this paper, we challenge this view and offer counter-arguments to both claims. We also argue that the possibility of establishing causal relations does not so much depend upon whether we use longitudinal or cross-sectional data, but rather on whether or not the modelling strategy is structural.

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          Most cited references38

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          Introduction to Meta-Analysis

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            Misunderstandings between experimentalists and observationalists about causal inference

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              Observational research methods. Research design II: cohort, cross sectional, and case-control studies

              C Mann (2003)
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                Author and article information

                Journal
                Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique
                Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique
                SAGE Publications
                0759-1063
                2070-2779
                April 2010
                April 22 2010
                April 2010
                : 106
                : 1
                : 5-18
                Affiliations
                [1 ]Demography, University of Louvain - Louvain-la-Neuve, Belgium,
                [2 ]Philosophy, University of Kent, UK
                [3 ]Statistics, University of Louvain - Louvain-la-Neuve, Belgium
                Article
                10.1177/0759106309360114
                a2045005-fd67-4c1a-9a9d-0e4af569b2f7
                © 2010

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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