dot-wilson_ci: Wilson score interval for a proportion
In survinger: Design-Adjusted Inference for Pathogen Lineage Surveillance
.wilson_ci R Documentation
Wilson score interval for a proportion
Description
Provides valid coverage even at p-hat = 0 or 1, unlike Wald.
Reference: Wilson (1927) JASA; Agresti & Coull (1998) TAS.
Usage
.wilson_ci(p, n, z, side = c("lower", "upper"))
Arguments
p
Estimated proportion.
n
Effective sample size.
z
Critical value (e.g., qnorm(0.975) for 95% CI).
side
Character: "lower" or "upper".
Value
Scalar bound, clamped to 0–1.
survinger documentation built on April 27, 2026, 9:10 a.m.
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| .wilson_ci | R Documentation |
Wilson score interval for a proportion
Description
Provides valid coverage even at p-hat = 0 or 1, unlike Wald. Reference: Wilson (1927) JASA; Agresti & Coull (1998) TAS.
Usage
.wilson_ci(p, n, z, side = c("lower", "upper"))
Arguments
p |
Estimated proportion. |
n |
Effective sample size. |
z |
Critical value (e.g., qnorm(0.975) for 95% CI). |
side |
Character: "lower" or "upper". |
Value
Scalar bound, clamped to 0–1.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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