tp.normal: Normal approximation confidence limits for true prevalence

In RSurveillance: Design and Analysis of Disease Surveillance Activities

Description

Estimates true prevalence and confidence limits for estimates based on normal approximation

Usage

tp.normal(x, n, se, sp, conf = 0.95)

Arguments

x	number of positive results in sample (scalar or vector)
n	sample size (scalar or vector)
se	test unit sensitivity (scalar or vector)
sp	test unit specificity (scalar or vector)
conf	desired level of confidence for CI, default = 0.95 (scalar or vector)

Value

list with 2 elements, a matrix of apparent prevalence and wilson lower and upper confidence limits and a matrix of true prevalence and normal approximation lower and upper confidence limits

Examples

# examples for tp.normal
tp.normal(25, 120, 0.9, 0.99)
tp.normal(seq(5, 25, by=5), 120, 0.9, 0.99)

RSurveillance documentation built on July 2, 2020, 2:33 a.m.