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Erschienen in: Social Psychiatry and Psychiatric Epidemiology 2/2017

08.02.2017 | Commentary

Commentary: on the application of potential outcomes-based methods to questions in social psychiatry and psychiatric epidemiology

verfasst von: Sharon Schwartz

Erschienen in: Social Psychiatry and Psychiatric Epidemiology | Ausgabe 2/2017

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Excerpt

Two papers in this issue, “Disparities at the Intersection of Marginalized Groups” [1] and “Causal Inference and Longitudinal Data: A Case Study of Religion and Mental Health” [2], provide compelling arguments for the utility of methods grounded in a potential outcomes framework in social and psychiatric epidemiology. While these methods can sometimes seem complex, the authors provide very clear and accessible guidance for their use. …
Fußnoten
1
The authors of this paper seem somewhat ambivalent about the causal status of the effect estimated. On the one hand, there is a disclaimer that the paper only estimated an association, but on the other they interpret the results of the decomposition model as estimating the effect that was due to race alone, due to SES alone, and due to the intersection of race and SES. This certainly seems like a causal attribution. Indeed, the authors clearly state that the study results are applicable when “disparities are taken to represent causal effects of race and SES, when proper adjustment has been made for confounding variables”. Therefore we are assuming that the interpretation was for an estimate where confounder control was in effect, and the association disclaimer is just a “technical” issue in this particular analysis.
 
Literatur
2.
Zurück zum Zitat VanderWeele TJ, Jackson JW, Li S (2016) Causal inference and longitudinal data: a case study of religion and mental health. Soc Psychiatry Psychiatric Epidemiol 51(11):1457–1466. doi:10.1007/s00127-016-1281-9 CrossRef VanderWeele TJ, Jackson JW, Li S (2016) Causal inference and longitudinal data: a case study of religion and mental health. Soc Psychiatry Psychiatric Epidemiol 51(11):1457–1466. doi:10.​1007/​s00127-016-1281-9 CrossRef
5.
Zurück zum Zitat Holland PW (1986) Statistics and Causal Inference. J Amer Statistical Assoc 81:945–960CrossRef Holland PW (1986) Statistics and Causal Inference. J Amer Statistical Assoc 81:945–960CrossRef
6.
Zurück zum Zitat Hernán MA, Robins JM (2017) Causal inference. Chapman & Hall/CRC, Boca Raton (forthcoming) Hernán MA, Robins JM (2017) Causal inference. Chapman & Hall/CRC, Boca Raton (forthcoming)
9.
Zurück zum Zitat Naimi AI, Kaufman JS (2015) Counterfactual theory in social epidemiology: reconciling analysis and action for the social determinants of health. Curr Epidemiol Rep 2(1):52–60. doi:10.1007/s40471-014-0030-4 CrossRef Naimi AI, Kaufman JS (2015) Counterfactual theory in social epidemiology: reconciling analysis and action for the social determinants of health. Curr Epidemiol Rep 2(1):52–60. doi:10.​1007/​s40471-014-0030-4 CrossRef
10.
Zurück zum Zitat VanderWeele TJ (2015) Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford University Press, New York VanderWeele TJ (2015) Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford University Press, New York
14.
Zurück zum Zitat Hernán MA, Taubman SL (2008) Does obesity shorten life? The importance of well-defined interventions to answer causal questions. Int J Obesity (2005) 32 Suppl 3:S8–S14. doi:10.1038/ijo.2008.82 CrossRef Hernán MA, Taubman SL (2008) Does obesity shorten life? The importance of well-defined interventions to answer causal questions. Int J Obesity (2005) 32 Suppl 3:S8–S14. doi:10.​1038/​ijo.​2008.​82 CrossRef
Metadaten
Titel
Commentary: on the application of potential outcomes-based methods to questions in social psychiatry and psychiatric epidemiology
verfasst von
Sharon Schwartz
Publikationsdatum
08.02.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Social Psychiatry and Psychiatric Epidemiology / Ausgabe 2/2017
Print ISSN: 0933-7954
Elektronische ISSN: 1433-9285
DOI
https://doi.org/10.1007/s00127-016-1334-0

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