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Confounded by confounding: separating association from causation
Hospital Medicine, 1999Health-care professionals need to be able to distinguish causal relationships from simple associations in two main areas: when unravelling the aetiology of diseases, and when assessing the effects of therapies. In each of these the presence of confounding can seriously mislead. This short report explains the nature of confounding and outlines criteria
Davies, Huw T. O., Williams, Fiona L .R.
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, 2001 Bij observationeel onderzoek is het vaak lastig om te weten van welke risicofactor een geconstateerd effect afkomstig is. Vermenging van effect van verschillende risicofactoren is daarvan vaak de oorzaak. Confounding betekent letterlijk verwarring of verstoring.
Buitendijk, S.E., Miranda, E. de
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2018
An apparent relationship between a disease and a risk factor may be explained (confounded) by their joint association with an intermediate third ‘true’ risk factor. The issue here is not one of impaired validity; if the study had been carefully conducted then the relationship observed was correct and the problem of confounding is therefore one of ...
Alan J. Silman +2 more
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An apparent relationship between a disease and a risk factor may be explained (confounded) by their joint association with an intermediate third ‘true’ risk factor. The issue here is not one of impaired validity; if the study had been carefully conducted then the relationship observed was correct and the problem of confounding is therefore one of ...
Alan J. Silman +2 more
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American journal of epidemiology, 1987
Miettinen and Cook (Am J Epidemiol 1981;114:593-603) postulate that confounding is a result of exposure-strata dependence in the joint source population, irrespective of the effective parameter used. Boivin and Wacholder (Am J Epidemiol 1985;121:152-8) postulate that confounding is dependent on the additive structure of the crude effect parameter. Both
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Miettinen and Cook (Am J Epidemiol 1981;114:593-603) postulate that confounding is a result of exposure-strata dependence in the joint source population, irrespective of the effective parameter used. Boivin and Wacholder (Am J Epidemiol 1985;121:152-8) postulate that confounding is dependent on the additive structure of the crude effect parameter. Both
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Using negative controls to adjust for unmeasured confounding bias in time series studies
Nature Reviews Methods Primers, 2023Jie Kate Hu, Francesca Dominici
exaly