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Calculate Standard Error and Confidence Interval for a Proportion

se_p.Rd

This function computes the standard error and the asymptotic (Wald) confidence interval for a given proportion based on a specified number of simulations or observations.

Usage

se_p(p, nsim, conf.level = 0.95)

Arguments

p

A numeric value representing the proportion (between 0 and 1).

nsim

An integer representing the number of simulations or the sample size.

conf.level

A numeric value between 0 and 1 specifying the confidence level for the interval. Defaults to 0.95.

Value

A list containing:

  • se: The calculated standard error of the proportion.

  • ci: A named numeric vector with the lower bound (ci.lb) and upper bound (ci.ub) of the confidence interval.

Details

The standard error is calculated as: $$SE = \sqrt{\frac{p(1-p)}{n}}$$ The confidence interval is calculated using the standard normal distribution (Z-score) approximation.

Examples

se_p(p = 0.5, nsim = 1000)
#> $se
#> [1] 0.01581139
#> 
#> $ci
#>     ci.lb     ci.ub 
#> 0.4690102 0.5309898 
#> 
se_p(p = 0.2, nsim = 500, conf.level = 0.99)
#> $se
#> [1] 0.01788854
#> 
#> $ci
#>     ci.lb     ci.ub 
#> 0.1539222 0.2460778 
#>