epi.ssdxsesp {epiR} R Documentation

## Sample size to estimate the sensitivity or specificity of a diagnostic test

### Description

Sample size to estimate the sensitivity or specificity of a diagnostic test.

### Usage

```epi.ssdxsesp(test, type = "se", Py, epsilon, error = "relative",
nfractional = FALSE, conf.level = 0.95)
```

### Arguments

 `test` scalar number, the prior estimate of diagnostic test performance (0 to 1). `type` character string. Options are `se` to estimate a sample size to determine diagnostic sensitivity and `sp` to estimate a sample size to determine diagnostic specificity. `Py` scalar number, an estimate of the prevalence of the outcome in the study population. `epsilon` scalar number, the maximum difference between the estimate and the unknown population value expressed in absolute or relative terms. `error` character string. Options are `absolute` for absolute error and `relative` for relative error. `nfractional` logical, return fractional sample size. `conf.level` scalar number, the level of confidence in the computed result.

### Value

Returns an integer defining the required sample size.

### Note

The sample size calculation method implemented in this function follows the approach described by Hajian-Tilaki (2014).

### References

Hajian-Tilaki K (2014). Sample size estimation in diagnostic test studies of biomedical informatics. Journal of Biomedical Informatics 48: 193 - 204. DOI: 10.1016/j.jbi.2014.02.013.

### Examples

```## EXAMPLE 1 (from Hajian-Tilaki 2014, p 195):
## A new diagnostic test has been developed and we'd like to conduct a study
## to determine its diagnostic sensitivity which we believe should be in the
## order of 0.80. How many subjects should be enrolled if the prevalence of
## the disease outcome of interest is 0.10 and we'd like to be 95% confident
## that our estimate of sensitivity is within 0.07 of the true population
## value?

epi.ssdxsesp(test = 0.80, type = "se", Py = 0.10, epsilon = 0.07,
error = "absolute", nfractional = FALSE, conf.level = 0.95)

## A total of 1255 subjects need to be enrolled to meet the requirements of the
## study.
```

[Package epiR version 2.0.38 Index]