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Herkkyys ja spesifisyys×P-arvo ja tilastollinen merkitsevyys×
TieteenalaTutkimuksen tilastomenetelmätTutkimuksen tilastomenetelmät
MenetelmäperheProcess / pipelineProcess / pipeline
Syntyvuosi19781925
KehittäjäMultiple sources in medical diagnosis and signal detectionRonald Fisher
TyyppiConceptConcept
AlkuperäislähdeAltman, D. G., & Bland, J. M. (1994). Diagnostic tests 1: Sensitivity and specificity. BMJ, 308(6943), 1552. link ↗Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. link ↗
Rinnakkaisnimetdiagnostic accuracy, true positive rate, true negative rate, receiver operating characteristicp-value, significance test, statistical significance, alpha level
Liittyvät45
TiivistelmäSensitivity and specificity are fundamental metrics of diagnostic test accuracy. Sensitivity is the probability that a test correctly identifies a person with the disease (true positive rate: TP / (TP + FN)). Specificity is the probability that a test correctly identifies a person without the disease (true negative rate: TN / (TN + FP)). Every test involves a trade-off: increasing sensitivity (catching all sick people) often reduces specificity (more false alarms). Choice of test threshold depends on the clinical context: screening for serious diseases favors sensitivity; confirming a diagnosis favors specificity.The p-value is the probability of observing data as extreme as or more extreme than what was actually observed, assuming the null hypothesis is true. Introduced by Ronald Fisher in 1925, it is the foundation of frequentist hypothesis testing. Statistical significance is declared when the p-value falls below a pre-specified threshold (alpha level, typically 0.05).
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ScholarGateVertaile menetelmiä: Sensitivity and Specificity · P-Value and Statistical Significance. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare