Selecting Confounders from Covariates

Gillian M. Raab

Journal of the Royal Statistical Society Series A, 1994, vol. 157, issue 2, 271-283

Abstract: Most analyses of observational studies to investigate the relationship between a risk factor and an outcome use some data‐dependent method to select a subset of the available covariates to include as confounders. This paper evaluates methods which can be used to make this selection in linear models. The methods are applied to the selection of covariates in a study of the effect of lead in the blood on children's ability and are evaluated by a simulation study on multivariate normal data. None of the methods can be guaranteed to give satisfactory results in all cases, and all the methods can result in misleading inferences. Recommendations for the design and analysis of observational studies are made in the light of these results.

Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.2307/2983362

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:157:y:1994:i:2:p:271-283

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-985X

Access Statistics for this article

Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples

More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().