These methods use frequentist approaches to estimate prevalence and confidence limits, assuming a fixed pool size and a test with known values for sensitivity and specificity, as described below.
Diese Methode (Methode 4 vonCowling et al. (1999) assumes a fixed pool size and that test sensitivity and specificity are known exactly (no uncertainty about their values). Confidence limits are based on a normal approximation and may be <0 for low prevalence values.
Prävalenz wird geschätzt als:
und der Standardfehler (SE (p)) wird als Quadratwurzel der Varianz geschätzt, gegeben durch:
where:
Asymptotische Konfidenzgrenzen werden mit der normalen Näherung berechnet:
where ist die standardisierte Normalvariable, die der gewünschten Konfidenzgrenze entspricht.
Erforderliche Eingaben für diese Methode sind:
Pool size, number of pools and number of pools positive must be positive integers and the number of positive pools must be less than the number of pools tested. Sensitivity and specificity must be >0 and <=1 and upper and lower confidence limits must be >0 and <1.
Ausgänge include:
Estimates are only valid if the proportion of positive pools is greater than the false positive rate (1 - Specificity) and less than or equal to the true positive rate (Sensitivity). Invalid results are indicated by NA in the results table.
Diese Methode (Methode 5 vonCowling et al. (1999)) setzt eine feste Poolgröße voraus und dass die Testempfindlichkeit und -spezifität genau bekannt sind (keine Unsicherheit über ihre Werte). Genaue Konfidenzgrenzen werden auf der Grundlage der Binomialtheorie berechnet, sodass Konfidenzgrenzen niemals <0 oder >1.
Prävalenz und Varianz werden wie fürMethode 3:
und:
where:
Exact confidence limits are estimated by calculating the corresponding binomial confidence limits for the proportion of positive pools and then transforming these back to individual-level prevalence values using the equation for estimating prevalence from Methode 3.
Erforderliche Eingaben für diese Methode sind:
Pool size, number of pools and number of pools positive must be positive integers and the number of positive pools must be less than the number of pools tested. Sensitivity and specificity must be >0 and <=1 and upper and lower confidence limits must be >0 and <1.
Ausgänge include:
Estimates are only valid if the proportion of positive pools is greater than the false positive rate (1 - Specificity) and less than or equal to the true positive rate (Sensitivity). Invalid results are indicated by NA in the results table.