- AutorIn
- Michael Höfler
- Tanja Brueck
- Roselind Lieb
- Hans-Ulrich Wittchen
- Titel
- Calculating control variables with age at onset data to adjust for conditions prior to exposure
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa-105363
- Quellenangabe
- Social Psychiatry and Psychiatric Epidemiology, Bd. 40 (2005), Nr. 9, S. 731-736, ISSN: 0933-7954
- Erstveröffentlichung
- 2005
- Abstract (EN)
- Background: When assessing the association between a factor X and a subsequent outcome Y in observational studies, the question that arises is what are the variables to adjust for to reduce bias due to confounding for causal inference on the effect of X on Y. Disregarding such factors is often a source of overestimation because these variables may affect both X and Y. On the other hand, adjustment for such variables can also be a source of underestimation because such variables may be the causal consequence of X and part of the mechanism that leads from X to Y. Methods: In this paper, we present a simple method to compute control variables in the presence of age at onset data on both X and a set of other variables. Using these age at onset data, control variables are computed that adjust only for conditions that occur prior to X. This strategy can be used in prospective as well as in survival analysis. Our method is motivated by an argument based on the counterfactual model of a causal effect. Results: The procedure is exemplified by examining of the relation between panic attack and the subsequent incidence of MDD. Conclusions: The results reveal that the adjustment for all other variables, irrespective of their temporal relation to X, can yield a false negative result (despite unconsidered confounders and other sources of bias).
- Andere Ausgabe
- DOI: 10.1007/s00127-005-0944-8
- Link zur publizierten Version des Artikels, der in der Zeitschrift "Social Psychiatry and Psychiatric Epidemiology" des Springer-Verlags erschienen ist.
Link: http://dx.doi.org/10.1007/s00127-005-0944-8 - Freie Schlagwörter (DE)
- Störfaktor, Kausalität, kausale Inferenz, Erkrankungsalter, logistische Regression, Lebensdaueranalyse, psychische Störungen, Epidemiologie
- Freie Schlagwörter (EN)
- confounding, causality, causal inference, age at onset, logistic regression, survival analysis, mental disorders, epidemiology
- Klassifikation (DDC)
- 150.2
- Klassifikation (RVK)
- CS 1000
- Publizierende Institution
- Technische Universität Dresden, Dresden
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa-105363
- Veröffentlichungsdatum Qucosa
- 20.02.2013
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis