International Journal of Epidemiology 2001;30:421-422
© International Epidemiological Association 2001
Editorial |
A renaissance for measurement error
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 one in someone else's study. As epidemiologists we spend our days chasing the confounder like detectives, anticipating its disturbing appearance when designing a study, considering potential confounders in our analysis, and trying to illuminate unconsidered or residual confounders when the results of our study do not conform with the expected.1
Other toys have also come to occupy our minds. Advanced and fancy analytical methods increasingly find their way into epidemiological analyses. They challenge the epidemiologist and impress the reader. Some real progress has been made with using more refined methods such as hierarchical models,2 structural causal models,3 and the improved graphical display of data.4
But when we contemplate how to further improve our trade maybe we have to regress to our roots
Notes
References
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. Eluf-Neto Re: "Determinants of Quality of Interview and Impact on Risk Estimates in a Case-Control Study of Bladder Cancer" Am. J. Epidemiol., November 15, 2009; 170(10): 1319 - 1319. [Full Text] [PDF]
|
|
|
|
 |
|
 K. B. Michels, C. S. Fuchs, E. Giovannucci, G. A. Colditz, D. J. Hunter, M. J. Stampfer, and W. C. Willett Fiber Intake and Incidence of Colorectal Cancer among 76,947 Women and 47,279 Men Cancer Epidemiol. Biomarkers Prev., April 1, 2005; 14(4): 842 - 849. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L Myer, C Morroni, and B G Link Impact of measurement error in the study of sexually transmitted infections Sex Transm Inf, August 1, 2004; 80(4): 318 - 321. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. B. Michels, S. A. Bingham, R. Luben, A. A. Welch, and N. E. Day The Effect of Correlated Measurement Error in Multivariate Models of Diet Am. J. Epidemiol., July 1, 2004; 160(1): 59 - 67. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. W. Vernon, H. Meissner, C. Klabunde, B. K. Rimer, D. J. Ahnen, R. Bastani, M. T. Mandelson, M. R. Nadel, S. Sheinfeld-Gorin, and J. Zapka Measures for Ascertaining Use of Colorectal Cancer Screening in Behavioral, Health Services, and Epidemiologic Research Cancer Epidemiol. Biomarkers Prev., June 1, 2004; 13(6): 898 - 905. [Full Text] [PDF]
|
|
|
|
 |
|
 K. B Michels Nutritional epidemiology--past, present, future Int. J. Epidemiol., August 1, 2003; 32(4): 486 - 488. [Full Text] [PDF]
|
|
|
|
 |
|
 J. D Kark, N. A Kaufmann, F. Binka, N. Goldberger, and E. M Berry Adipose tissue n-6 fatty acids and acute myocardial infarction in a population consuming a diet high in polyunsaturated fatty acids Am. J. Clinical Nutrition, April 1, 2003; 77(4): 796 - 802. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. B. Michels and E. Braunwald Estimating Treatment Effects From Observational Data: Dissonant and Resonant Notes From the SYMPHONY Trials JAMA, June 19, 2002; 287(23): 3130 - 3132. [Full Text] [PDF]
|
|
|
|
|
|
E Fernandez-Jarne, E Martinez-Losa, M Prado-Santamaria, C Brugarolas-Brufau, M Serrano-Martinez, and M. Martinez-Gonzalez Risk of first non-fatal myocardial infarction negatively associated with olive oil consumption: a case-control study in Spain Int. J. Epidemiol., April 1, 2002; 31(2): 474 - 480. [Abstract] [Full Text] [PDF]
|
|