A renaissance for measurement error

doi:10.1093/ije/30.3.421

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International Journal of Epidemiology 2001;30:421-422
© International Epidemiological Association 2001

Editorial

A renaissance for measurement error

Karin B Michels

Our best friend in epidemiology, it seems, is the confounder.The confounder preoccupies our thinking, we respect its omnipresence,and we are endlessly entertained by attempting to identify onein someone else's study. As epidemiologists we spend our dayschasing the confounder like detectives, anticipating its disturbingappearance when designing a study, considering potential confoundersin our analysis, and trying to illuminate unconsidered or residualconfounders when the results of our study do not conform withthe expected.¹

Other toys have also come to occupy our minds. Advanced andfancy analytical methods increasingly find their way into epidemiologicalanalyses. They challenge the epidemiologist and impress thereader. Some real progress has been made with using more refinedmethods such as hierarchical models,² structural causal models,³and the improved graphical display of data.⁴

But when we contemplate how to further improve our trade maybewe have to regress to our roots . . . [Full Text of this Article]

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