Information bias (epidemiology)

1 Definition
2 Misclassification
- 2.1 Non differential misclassification
- 2.2 Differential misclassification
3 References

Definition

Also referred to as observational bias and misclassification. A Dictionary of Epidemiology, sponsored by the International Epidemiological Association, defines this as the following:

“1. A flaw in measuring exposure, covariate, or outcome variables that results in different quality (accuracy) of information between comparison groups. The occurrence of information biases may not be independent of the occurrence of selection biases.

2. Bias in an estimate arising from measurement errors.”^[1]

Information bias, essentially, refers to bias arising from measurement error.^[2]

Misclassification

Misclassification thus refers to measurement error. There are two types of misclassification in epidemiological research: non differential misclassification and differential misclassification.

Non differential misclassification

Non differential misclassification is when all classes, groups, or categories of a variable (whether exposure, outcome, or covariate) have the same error rate or probability of being misclassified for all study subjects.^[1] The traditional assumption has been that, in the case of binary or dichotomous variables, this would result in an underestimate of the hypothesized relationship between exposure and outcome. This has more recently been challenged however in that results of individual studies represent a single estimate and not the average of repeated measurements and thus can be farther (or nearer) from the null value (i.e. zero) than the true value.^[3]

Differential misclassification

Differential misclassification occurs when the error rate or probability of being misclassified differs across groups of study subjects.^[1] 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. The effect(s) of such misclassification can vary from an overestimation to an underestimation of the true value.^[4] Statisticians have developed methods to adjust for this type of bias, which may assist somewhat in compensating for this problem when known and when it is quantifiable.^[5]

References

^ ^a ^b ^c Porta M, editor. "A Dictionary of Epidemiology." 5th edition. Oxford University Press, 2008, p. 128.
^ Rothman K, Greenland S, Lash T. "Modern Epidemiology." 3rd edition. Lipincott Williams and Wilkins, 2008, p.137.
^ Jurek AM, Greenland S, Maldonado G, Church TR. "Proper interpretation of non-differential misclassification effects: expectations vs observations." "International Journal of Epidemiology" 2005; 34:680-7, accessed May 4th 2011.
^ Copeland KT, Checkoway H, McMichael AJ, Holbrook A. "Bias due to misclassification in the estimation of relative risk." "American Journal of Epidemiology" 1977; 105(5):488-95, accessed May 4th 2011.
^ Greenland S. "Variance estimation for epidemiologic effect estimates under misclassification." "Statistics in Medicine" 1988; 745-57, accessed May 4th 2011.

Biases

Cognitive bias	Confirmation bias · Correspondence bias · Hindsight bias · Memory bias · Motivated reasoning · Outcome bias · Publication bias · Status quo bias

Statistical bias	Ascertainment bias · Bias of an estimator · Information bias · Lead time bias · Observer bias · Omitted-variable bias · Recall bias · Response bias · Sampling bias · Selection bias · Systematic bias · Systemic bias

Other/ungrouped	FUTON bias · No abstract available bias