2010
DOI: 10.1136/bmj.c2289
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Random measurement error and regression dilution bias

Abstract: Random measurement error is a pervasive problem in medical research, which can introduce bias to an estimate of the association between a risk factor and a disease or make a true association statistically non-significant. Hutcheon and colleagues explain when, why, and how random measurement error introduces bias and provides strategies for researchers to minimise the problem

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Cited by 618 publications
(535 citation statements)
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“…On the other hand, an underestimation of a true inverse association between F&V consumption and the risk of chronic disease may happen in any epidemiological study because of imprecise dietary measurements, regressiondilution bias (38) or limited between-subjects variability in F&V consumption (33) . Some degree of non-differential misclassification (measurement error) is unavoidable in nutritional epidemiology and may account for losing the ability to detect some real associations if they are not strong enough.…”
Section: Discussionmentioning
confidence: 99%
“…On the other hand, an underestimation of a true inverse association between F&V consumption and the risk of chronic disease may happen in any epidemiological study because of imprecise dietary measurements, regressiondilution bias (38) or limited between-subjects variability in F&V consumption (33) . Some degree of non-differential misclassification (measurement error) is unavoidable in nutritional epidemiology and may account for losing the ability to detect some real associations if they are not strong enough.…”
Section: Discussionmentioning
confidence: 99%
“…Procedures such as errors-in-variables regression can produce unbiased estimates, but rely on knowing the reliability or the within-person standard deviation to correct these effects. Hence our estimates are also important to those using such measures as confounding variables [12].…”
Section: Reliability Of Orthostatic Hypotension and Related Classificmentioning
confidence: 99%
“…Clinical diagnoses require repeatable and robust biomarkers with well characterised intra-and inter-individual variability [11], while in research, knowledge of measurement error is used in power calculations, to select outcome measures and to reduce errors associated with incomplete correction of confounding and regression dilution bias [12].…”
Section: Introductionmentioning
confidence: 99%
“…Regression dilution, due to the use of unreliable exposure measures generally causes attenuation of risk estimates. 40 The reliability of plasma vitamins and carotenoids has been estimated in a subsample of the two Dutch cohorts within EPIC previously. 41 The intraclass correlation coefficient (ICC) of two samples (measured 2-5 years apart) ranged between 0.17 for plasma a-tocopherol to 0.50 for vitamin C. These (moderately) low ICC values may have caused an underestimation of associations with CRC.…”
Section: Discussionmentioning
confidence: 99%