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Misclassification errors caused by imperfect sensitivity (U) and specificity (V) can affect statistical inferences in epidemiology. Such errors can lead to biases and increased standard errors in estimates of rates. Furthermore, low U and V can have a catastrophic effect on the power of a test to detect a change in rate, and, if U and V change even slightly as the rate changes, the effect on power may be dramatic.
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Quade et al. (1980) studied this question.
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