Description Usage Arguments Value Examples
View source: R/prevalence_functions.R
Calculates Agresti-Coull confidence limits for a simple proportion (apparent prevalence)
1 | binom.agresti(x, n, conf = 0.95)
|
x |
number of positives in sample |
n |
sample size, note: either x or n can be a vector, but at least one must be scalar |
conf |
level of confidence required, default 0.95 (scalar) |
a dataframe with 6 columns, x, n, proportion, lower confidence limit, upper confidence limit, confidence level and CI method
1 2 3 4 | # test binom.agresti
binom.agresti(25, 200)
binom.agresti(seq(10, 100, 10), 200)
binom.agresti(50, seq(100, 1000, 100))
|
x n proportion lower upper conf.level method
1 25 200 0.125 0.08558957 0.1785444 0.95 agresti-coull
x n proportion lower upper conf.level method
1 10 200 0.05 0.02626810 0.09069269 0.95 agresti-coull
2 20 200 0.10 0.06500984 0.15006642 0.95 agresti-coull
3 30 200 0.15 0.10670629 0.20648544 0.95 agresti-coull
4 40 200 0.20 0.15016868 0.26113852 0.95 agresti-coull
5 50 200 0.25 0.19489935 0.31452332 0.95 agresti-coull
6 60 200 0.30 0.24063696 0.36690117 0.95 agresti-coull
7 70 200 0.35 0.28722845 0.41842514 0.95 agresti-coull
8 80 200 0.40 0.33457989 0.46918917 0.95 agresti-coull
9 90 200 0.45 0.38263431 0.51925023 0.95 agresti-coull
10 100 200 0.50 0.43136086 0.56863914 0.95 agresti-coull
x n proportion lower upper conf.level method
1 50 100 0.50000000 0.40383153 0.59616847 0.95 agresti-coull
2 50 200 0.25000000 0.19489935 0.31452332 0.95 agresti-coull
3 50 300 0.16666667 0.12855765 0.21320433 0.95 agresti-coull
4 50 400 0.12500000 0.09592152 0.16121270 0.95 agresti-coull
5 50 500 0.10000000 0.07650314 0.12959633 0.95 agresti-coull
6 50 600 0.08333333 0.06362401 0.10834408 0.95 agresti-coull
7 50 700 0.07142857 0.05445670 0.09307860 0.95 agresti-coull
8 50 800 0.06250000 0.04759859 0.08158293 0.95 agresti-coull
9 50 900 0.05555556 0.04227472 0.07261430 0.95 agresti-coull
10 50 1000 0.05000000 0.03802202 0.06542206 0.95 agresti-coull
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