This function calculates the confidence interval for a proportion. It is vectorized, allowing users to evaluate it using either single values or vectors.
ci_p_arcsine(x, n, conf.level = 0.95)
A matrix with the lower and upper limits.
The expression to obtain the confidence interval is given below:
\(\sin^2(\hat\phi_{ML} \pm z_{\alpha/2} \times se(\hat\phi_{ML}))\),
where the maximum likelihood estimator for \(\phi\) is \(\hat\phi_{ML}=\arcsin(\sqrt{\hat \pi_{ML}})\), and its standard error is \(se(\hat{\phi}_{ML})=\frac{1}{\sqrt{4n}}\). The value \(z_{\alpha/2}\) is the \(1-\alpha/2\) percentile of the standard normal distribution (e.g., \(z_{0.025}=1.96\) for a 95% confidence interval).
Missing reference.
ci_p.
ci_p_arcsine(x=15, n=50, conf.level=0.95)
#> [,1]
#> [1,] 0.1822339
#> [2,] 0.4330338