# CI.BE: 1-2*alpha confidence interval given point estimate, CV, and n In PowerTOST: Power and Sample Size for (Bio)Equivalence Studies

 CI.BE R Documentation

## 1–2*alpha confidence interval given point estimate, CV, and n

### Description

Utility function to calculate the 1–2α CI given point estimate, CV, and n for the various designs covered in this package.

### Usage

```CI.BE(alpha = 0.05, pe, CV, n, design = "2x2", robust = FALSE)
```

### Arguments

 `alpha` Type I error probability, significance level. Defaults to 0.05. `pe` Point estimate (GMR). `CV` Coefficient of variation as ratio (not percent). `n` Total number of subjects if a scalar is given. Number of subjects in (sequence) groups if given as vector. `design` Character string describing the study’s design. See `known.designs()` for designs covered in this package. `robust` Defaults to `FALSE`. Setting to `TRUE` will use the degrees of freedom according to the ‘robust’ evaluation (aka Senn’s basic estimator). These degrees of freedom are calculated as `n-seq`. See `known.designs()\$df2` for designs covered in this package.

### Value

Returns the 1–2α confidence interval.
Returns a vector with named elements `lower`, `upper` if arguments `pe` and `CV` are scalars, else a matrix with columns `lower`, `upper` is returned.

### Note

The function assumes an evaluation using log-transformed data.
The function assumes equal variances in case of `design="parallel"` and the higher order crossover designs.
The implemented formula covers balanced and unbalanced designs.

Whether the function vectorizes properly is not thoroughly tested.

D. Labes

### Examples

```# 90% confidence interval for the 2x2 crossover
# n(total) = 24
CI.BE(pe = 0.95, CV = 0.3, n = 24)
# should give
#     lower     upper
# 0.8213465 1.0988055
# same total number but unequal sequences
CI.BE(pe = 0.95, CV = 0.3, n = c(13, 11))
#     lower     upper
# 0.8209294 1.0993637
```

PowerTOST documentation built on March 18, 2022, 5:47 p.m.