example of differential misclassification of exposure

For example, with SE of 0.95 and SP of 1 (s6)—roughly corresponding to measurement of smoking status using serum cotinine—nondifferential misclassification of exposure resulted in a small bias toward the null; but, overestimates of effect were observed in 46% of studies (n = 230 of 500). a For each combination of sensitivity and specificity, 500 studies with n = 5,000 were generated with probability of exposure of 0.10 and a true risk ratio of 2. Bias is not the difference between a particular study result and the truth—that is error. In these circumstances differential misclassification is likely to arise. Author affiliations: Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, Massachusetts (Brian W. Whitcomb); and Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania (Ashley I. Naimi). Epidemiology. So even though the measurement error was non-differential, the misclassification is differential and the direction is not necessarily towards the null. Copyright © 2021 Johns Hopkins Bloomberg School of Public Health. 1991;134(10):1233-44. Bias was toward the null in all scenarios with nondifferential misclassification of exposure (i.e., s2–s25). Non‐differential misclassification occurs when the degree of misclassification of exposure status among those with and those without the disease is the same; in cohort studies, this type of bias is most likely and will bias estimates toward no association when the exposure is dichotomized. 1994;5(5):510-7. All rights reserved. For full access to this pdf, sign in to an existing account, or purchase an annual subscription. T-Distribution Table (One Tail and Two-Tails), Variance and Standard Deviation Calculator, Permutation Calculator / Combination Calculator, The Practically Cheating Calculus Handbook, The Practically Cheating Statistics Handbook, https://www.statisticshowto.com/non-differential-misclassification/, Recall Bias: Definition, Examples, Strategies to Avoid it. Unless steps are taken to control for this possibility, emphysema will be under-diagnosed in non-smokers, which is a classification error because the diagnosis is related to the variable “how often smokers visit the doctor, versus non-smokers”. Springer Science & Business Media, Jul 26, 2007. RESEARCH ARTICLE Bias due to differential and non-differential disease- and exposure misclassification in studies of vaccine effectiveness Tom De Smedt1, Elizabeth Merrall2, Denis Macina3, Silvia Perez-Vilar4,5, Nick Andrews6, Kaatje Bollaerts1* 1 P95 Epidemiology and Pharmacovigilance, Leuven, Belgium, 2 GSK Vaccines, Amsterdam, The Netherlands, 3 Sanofi Pasteur, Lyon, France, 4 … For example, the accuracy of blood pressure measurement may be lower for heavier than for lighter study subjects, or a study of elderly persons may find that reports from elderly persons with dementia are less reliable than those without dementia. Example of non-differential misclassification (from Ahrens & Pigeot): Many studies ask if a patient has “ever used” a particular drug. Towards the Null means that the value is close to the null value of the effect measure. If smokers, because of concern about health effects … Need help with a homework or test question? In this case, the effect estimate was biased away from the null. These overestimates were generally small, but not always; in 1 of the data sets with SE of 0.4 and SP of 1 (s21), the RRz was 3.27, whereas the RRx was 2.52. The distinction between these 2 interpretations of nondifferentiality (i.e., equal occurrence vs. equal probability of misclassification) is more than just a matter of semantics. Brenner H, Blettner M. Misclassification bias arising from random error in exposure measurement: implications for dual measurement strategies. Am J Epidemiol. The degree and direction of differential misclassification vary with the exposure … As shown in the simulation study, in the specific setting of a dichotomous exposure with nondifferential misclassification of exposure and errors uncorrelated with outcomes, the result is a bias toward the null, as observed in a large number of study repetitions. For example, with SE of 0.95 and SP of 1 (s6)—roughly corresponding to measurement of smoking status using serum cotinine—nondifferential misclassification of exposure resulted in a small bias toward the null; but, overestimates of effect were observed in 46% of studies (n = 230 of 500). 1995;52(8):557-8. The misclassification of exposure or disease status can be considered as either differential or non-differential. Differential Exposure MisclassificationDifferential exposure misclassification occurs in case-control studies when the exposure misclassification errors for cases are not the same as those for controls. differential misclassification of exposure always leads to an underestimate of risk. Differential misclassification causes a bias in the risk Examples and mathematical results are presented to show that if the measurement error is nondifferential (independent of disease status), the resulting misclassification will often be differential, even in cohort studies. A bias away from the null would mean that the data is indicating a stronger association than actually exists in real life. More likely is this: Investigators design a study and measure exposure using an approach subject to misclassification that can reasonably be expected to be unrelated to outcomes. HOW DOES NONDIFFERENTIAL MISCLASSIFICATION OF EXPOSURE AFFECT AN INDIVIDUAL STUDY? Am J Epidemiol. Precisely this issue arises all the time. Oxford University Press is a department of the University of Oxford. Well people with a value of X’ close to the top of the category are more likely to develop the outcome than are people with values of X’ close to the bottom of the category. Jurek AM, Maldonado G, Greenland S, et al. For example, in practice, both exposure and disease status could be nondifferentially misclassified, yet misclassification could be dependent . Download PDF. Need to post a correction? The notion that nondifferential misclassification of exposure causes a bias toward the null and, therefore, results underestimate the true association is an oversimplification that is often not accurate. (1) Themostimportant andthe simplest point is that non-differential misclassifica-tion of a binary exposure (exposed or not) and a perfectly classified binary outcome (diseased ornot) doesindeedproducea bias toward the null. But, a single example does not provide information regarding how commonly such results may occur or why. differential misclassification in either cohort (their example) or case-control studies. Mark S Gilthorpe. By generating data for many studies from the same underlying truth, simulations enable evaluation of errors in individual studies, and of bias, as the average error from repeated studies. Geometric mean estimates were determined and compared to determine bias as the expected error across studies (Table 2). E.g., nuchal translucency test, BMI and subsequent stillbirth. 1993;138(6):453-61. Non-differential classification error is when the error does not depend on the values of other variables. https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model, Receive exclusive offers and updates from Oxford Academic, A Note on Correlated Errors in Exposure and Outcome in Logistic Regression, Obtaining Prevalence Estimates of COVID-19: A Model to Inform Decision-making, Invited Commentary: Toward Better Bias Analysis, Invited Commentary: Quantitative Bias Analysis can see the Forest for the Trees. Brenner H, Loomis D. Varied forms of bias due to nondifferential error in measuring exposure. Three real- -data sets taken from practical applications are used as examples to illustrate the methods. 1990;132(4):746-8. So now people with a high value of X’ are both more likely to be misclassified and also more likely to develop the outcome. So, we performed a simulation study generating 500 data sets, each with n = 5,000 for scenarios (s1–s25) with varying degrees of exposure-measurement error. Emphysema is a disease that may go undiagnosed without unusual medical attention. This is the commonly understood case of bias toward the null. Conclusions: Our findings suggest that, unlike nondifferential misclassification, differential misclassification of case-control status in a case-control study may not weaken the exposure-outcome association towarding the null hypothesis. This can be useful to illustrate misclassification; however, the notion of a data set that includes correct exposure, misclassified exposure, and outcomes for all individuals is implausible. In other words, the bias is different for exposed and non-exposed, or between those who have the disease and those do have not. With Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. Notably, even in circumstances where bias is always toward the null, our concern is interpretation of an individual study result in practice. However, interpreting nondifferential misclassification of exposure as exactly equal misclassification of exposure by outcome in a study is flawed. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide, This PDF is available to Subscribers Only. (In one special Non-differential misclassification bias: when the misclassification is the same across the groups to be compared, for example, exposure is equally misclassified in cases and controls. Errors in records, like incorrect disease codes, or patients completing questionnaires incorrectly (perhaps because they don’t remember (see: “. Nondifferential in this context means the probability of misclassification is the same in all study groups, for example, defined by outcome (2, 3). Probabilistic quantitative bias analysis has been described by various authors as an approach to provide insights about a plausible range of values for a measure of association. 1 5 Information bias • Non-differential misclassification – Results in a bias toward the null when the exposure or disease that is misclassified is binary – For example, when a binary exposure is measured with equal amount of error between case and control groups, it washes out the exposure-outcome association – This is a conservative bias, and the investigator at least knows that she/he is … Varying SE and SP, we calculated estimates for each of the 500 “studies” on the basis of true exposure |$({\hat{RR}}_X)$| and measured exposure |${\hat{( RR}}_Z$|⁠), considered errors in individual studies. However, even the simple case of nondifferential misclassification with a dichotomous exposure may be not so simple. 1. then the odds ratio will fall from 3.2 to 1.9. For instance, researchers use self-reported weight and height data to calculate BMI, but the calculated BMI has measurement error because of the self-report. However, investigators frequently face more basic issues that challenge proper interpretation of study results. independent of exposure, this is called non differential misclassification of outcome. It would be incorrect to describe this estimate as “biased away from the null.” Rather, this particular study resulted in an overestimate, regardless of any bias. Although care can be taken to minimize the impact of these errors, they are largely unavoidable because human error is innate to any study involving people. People who have a value of X’ close to the top of the category are more likely to be misclassified into the next higher category than are people with values of X’ close to the middle of the category. Classification criteria for tubulointerstitial nephritis with uveitis syndrome. In this case the magnitude of association in terms of common measures like the risk ratio 3) Counterintuitive effects of nondifferential misclassification of exposure. When the degree of misclassification of outcome is the same in the exposed vs unexposed groups, i.e. Differential misclassification occurs when the error rate or probability of being misclassified differs across groups of study subjects. Handbook of Epidemiology. Your first 30 minutes with a Chegg tutor is free! In studies of gene-environment interactions, exposure misclassification can lead to bias in the estimation of an interaction effect and increased sample size. Misclassification happens when some people are placed into the wrong group. And this can happen in prospective studies in which X is measured at baseline before the outcome has even occurred. But, it is also possible for unequal exposure misclassification to occur between outcome groups, such that the result overestimates the truth (Table 1, classification D). Classification criteria for multiple evanescent white dot syndrome. Using observed data and estimates for SE and SP, this kind of analysis can aid interpretation of findings by allowing for a degree of uncertainty in misclassification, as occurs in practice. Rothman, for example,states that "suchmis-classification canintroduceabias, butthebias is always in the direction ofunderestimating the effect",' and Checkoway et al state "non-differential misclassification of exposure will bias the effect estimate toward the null In a study affected by nondifferential misclassification of exposure but where misclassification is not exactly equal between cases and noncases, results can underestimate the true measure of effect (Table 1, classification C) if risks in observed exposure groups are more similar than when risks are compared between true exposure groups. As those for controls effects of nondifferential misclassification of exposure measurement error was non-differential, the term refers to bottom! The groups being compared account, or purchase an annual subscription length by et! 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