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Error and bias in observations 

Error and bias in observations
Error and bias in observations

Mark Elwood

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date: 20 April 2021

This chapter distinguishes error and bias, non-differential and differential misclassification distinguished. Non-differential misclassification almost always biases results toward the null, while differential misclassification can affect results in any direction. Methods to minimise observation bias include single, double and triple blind assessment. It discusses recall and other biases, with methods of assessment and avoidance, and practical issues on reducing error and bias. In part two, it shows how to measure and adjust for observational error and bias, including Kappa and adjusting for non-differential misclassification, and similar adjustments using continuous exposure measures. Effects with more than two categories of outcome or exposure, and of the misclassification of confounders are discussed. In assessing the accuracy of information, sensitivity, specificity, and predictive value are defined, and the calculation of the effects of misclassification using sensitivity and specificity are shown.

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