Abstract
The difference between test accuracy and predictive accuracy is presented and defined. The failure to distinguish between these two types of measures is shown to have led to a misguided debate over the interpretation of prevalence estimates. The distinction between test accuracy defined as sensitivity and specificity, and predictive accuracy defined as positive and negative predictive value is shown to reflect the choice of the denominator used to calculate true positive, false positive, false negative, and true negative rates. It is further shown that any instrument will tend to overestimate prevalence in low base rate populations and underestimate it in those populations where prevalence is high. The implications of these observations are then discussed in terms of the need to define diagnostic thresholds that have clinical and policy relevance.
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Gambino, B. Reflections on Accuracy. J Gambl Stud 22, 393–404 (2006). https://doi.org/10.1007/s10899-006-9025-5
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DOI: https://doi.org/10.1007/s10899-006-9025-5