ciAssessment {Rariant} | R Documentation

## Assessment of CI methods

### Description

Functions to compute the coverage probability of a confidence interval method.

### Usage

      coverageProbability(pars, fun = acCi, n_sample = 1e4, min_k, ...)

### Arguments

`pars` | Data frame with parameter combinations [data.frame]
`n_sample` | Number of assessments per parameter combination [integer(1)].
`fun` | CI function
`min_k` | Minimum 'k2' value to use.
`...` | Additional arguments that are passed on to 'fun'.

### Value

The 'data.frame' object 'pars' with additional columns 'cp' for the coverage probability and 'aw' average confidence interval width.

### References

Fagerland, Morten W., Stian Lydersen, and Petter Laake. Recommended Confidence Intervals for Two Independent Binomial Proportions. Statistical Methods in Medical Research (2011).

### Examples

    ## Define parameter space
    pars = expand.grid(k1 = 1:5, k2 = 5, n1 = 30, n2 = 30)
    conf_level = 0.95

    ## Compute coverage probabilities
    cp = coverageProbability(pars, fun = acCi, n_sample = 1e2, conf_level = conf_level)
    print(cp)

[Package Rariant version 1.16.0 Index]