ci_clopper_pearson: Clopper-Pearson confidence interval for binary data
In erplots: Model-Agnostic Exposure-Response Plots
View source: R/utils-helpers.R
ci_clopper_pearson R Documentation
Clopper-Pearson confidence interval for binary data
Description
Computes an exact binomial confidence interval for a proportion.
Usage
ci_clopper_pearson(x, n, conf_level = 0.95)
Arguments
x
Number of successes
n
Total number of trials
conf_level
Confidence level
Details
Used by the quantile-binned summary layer (see er_plot_add_quantiles())
to compute empirical response-rate confidence intervals. This assumes a
binary (0/1) response.
Value
Named numeric vector, with confidence level stored as an attribute
Examples
ci_clopper_pearson(1, 10)
erplots documentation built on Oct. 4, 2026, 5:06 p.m.
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View source: R/utils-helpers.R
| ci_clopper_pearson | R Documentation |
Clopper-Pearson confidence interval for binary data
Description
Computes an exact binomial confidence interval for a proportion.
Usage
ci_clopper_pearson(x, n, conf_level = 0.95)
Arguments
x |
Number of successes |
n |
Total number of trials |
conf_level |
Confidence level |
Details
Used by the quantile-binned summary layer (see er_plot_add_quantiles())
to compute empirical response-rate confidence intervals. This assumes a
binary (0/1) response.
Value
Named numeric vector, with confidence level stored as an attribute
Examples
ci_clopper_pearson(1, 10)
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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