Literature DB >> 3570609

Comparison of relative risks obtained in ecological and individual studies: some methodological considerations.

S Richardson, I Stücker, D Hémon.   

Abstract

This paper is concerned with the problem of estimating relative risks from ecological correlation studies. In the first part, some of the biases encountered when analysing aggregated data are discussed and in particular attention is focused on the shape of the dose-response relationship obtained from aggregated and non-aggregated data, on the need for extrapolation and on the scale of aggregation. In the second part some empirical observations are made on these points by means of four examples concerning the relative risk between smoking and different pathologies. The estimates of relative risks derived from French geographical data and from case control or cohort studies are compared. The performance of ecological studies is discussed with respect to the strength of the risk factor considered, the geographical distribution of counfounding factors and the adjustment of different models.

Mesh:

Year:  1987        PMID: 3570609     DOI: 10.1093/ije/16.1.111

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  27 in total

1.  Migration bias in ecologic studies.

Authors:  S Tong
Journal:  Eur J Epidemiol       Date:  2000-04       Impact factor: 8.082

2.  Geographical pattern of brain cancer incidence in the Navarre and Basque Country regions of Spain.

Authors:  G López-Abente; M Pollán; E Ardanaz; M Errezola
Journal:  Occup Environ Med       Date:  2003-07       Impact factor: 4.402

3.  Ecological Inference in the Social Sciences.

Authors:  Adam Glynn; Jon Wakefield
Journal:  Stat Methodol       Date:  2010-05-01

Review 4.  Designs for the combination of group- and individual-level data.

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Journal:  Epidemiology       Date:  2011-05       Impact factor: 4.822

5.  Incorporating marginal covariate information in a nonparametric regression model for a sample of R x C tables.

Authors:  Joan G Staniswalis
Journal:  Biometrics       Date:  2008-03-07       Impact factor: 2.571

6.  Multi-level modelling, the ecologic fallacy, and hybrid study designs.

Authors:  Jon Wakefield
Journal:  Int J Epidemiol       Date:  2009-04       Impact factor: 7.196

7.  State-level relationships cannot tell us anything about individuals.

Authors:  Alex H S Harris; Keith Humphreys; John W Finney
Journal:  Am J Public Health       Date:  2015-02-25       Impact factor: 9.308

8.  Incorporating spatial variability within epidemiological studies of environmental exposures.

Authors:  Gavin Shaddick; Duncan Lee; Jonathan Wakefield
Journal:  Int J Appl Earth Obs Geoinf       Date:  2013-06

9.  Bayes computation for ecological inference.

Authors:  Jon Wakefield; Sebastien Haneuse; Adrian Dobra; Elizabeth Teeple
Journal:  Stat Med       Date:  2011-02-22       Impact factor: 2.373

Review 10.  Cancer differentials among US blacks and whites: quantitative estimates of socioeconomic-related risks.

Authors:  K M Gorey; J E Vena
Journal:  J Natl Med Assoc       Date:  1994-03       Impact factor: 1.798

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