# sensspec: Sample size and precision of sensitivity and specificity In presize: Precision Based Sample Size Calculation

## Description

Because sensitivity and specificity are simple proportions, these functions act as wrappers for `prec_prop`.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```prec_sens( sens, n = NULL, ntot = NULL, prev = NULL, conf.width = NULL, round = "ceiling", ... ) prec_spec( spec, n = NULL, ntot = NULL, prev = NULL, conf.width = NULL, round = "ceiling", ... ) ```

## Arguments

 `sens, spec` proportions. `n` number of observations. `ntot` total sample size. `prev` prevalence of cases/disease (i.e. proportion of `ntot` with the disease). `conf.width` precision (the full width of the confidence interval). `round` string, round calculated `n` up (`ceiling`) or down (`floor`). `...` options passed to prec_prop (e.g. method, conf.width, conf.level).

## Details

If `ntot` and `prev` are given, they are used to calculate `n`.

## Value

Object of class "presize", a list of arguments (including the computed one) augmented with method and note elements.

## Note

Calculated `n` can take on non-integer numbers, but `prec_prop` requires integers, so the calculated `n` is rounded according to the approach indicated in `round`.

`prec_prop`
 ```1 2 3 4 5 6``` ``` # confidence interval width with n prec_sens(.6, 50) # confidence interval width with ntot and prevalence (assuming 50% prev) prec_sens(.6, ntot = 100, prev = .5) # sample size with confidence interval width prec_sens(.6, conf.width = 0.262) ```