# power.prop1.test: Power Calculations for One-Sample Test for Proportions In MKpower: Power Analysis and Sample Size Calculation

## Description

Compute the power of the one-sample test for proportions, or determine parameters to obtain a target power.

## Usage

 ```1 2 3 4``` ```power.prop1.test(n = NULL, p1 = NULL, p0 = 0.5, sig.level = 0.05, power = NULL, alternative = c("two.sided", "less", "greater"), cont.corr = TRUE, tol = .Machine\$double.eps^0.25) ```

## Arguments

 `n` number of observations (per group) `p1` expected probability `p0` probability under the null hypothesis `sig.level` significance level (Type I error probability) `power` power of test (1 minus Type II error probability) `alternative` one- or two-sided test. Can be abbreviated. `cont.corr` use continuity correction `tol` numerical tolerance used in root finding, the default providing (at least) four significant digits.

## Details

Exactly one of the parameters `n`, `p1`, `power`, and `sig.level` must be passed as NULL, and that parameter is determined from the others. Notice that `sig.level` has a non-NULL default so `NULL` must be explicitly passed if you want it computed.

The computation is based on the asymptotic formulas provided in Section 2.5.1 of Fleiss et al. (2003). If `cont.corr = TRUE` a continuity correction is applied, which may lead to better approximations of the finite-sample values.

## Value

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

## Note

The documentation was adapted from `power.prop.test`.

## Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

## References

J.L. Fleiss, B. Levin and M.C. Paik (2003). Statistical Methods for Rates and Proportions. Wiley Series in Probability and Statistics.

`power.prop.test`, `prop.test`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```power.prop1.test(p1 = 0.4, power = 0.8) power.prop1.test(p1 = 0.4, power = 0.8, cont.corr = FALSE) power.prop1.test(p1 = 0.6, power = 0.8) power.prop1.test(n = 204, power = 0.8) power.prop1.test(n = 204, p1 = 0.4, power = 0.8, sig.level = NULL) power.prop1.test(n = 194, p1 = 0.4, power = 0.8, sig.level = NULL, cont.corr = FALSE) power.prop1.test(p1 = 0.1, p0 = 0.3, power = 0.8, alternative = "less") power.prop1.test(p1 = 0.1, p0 = 0.3, power = 0.8, alternative = "less", cont.corr = FALSE) power.prop1.test(n = 31, p0 = 0.3, power = 0.8, alternative = "less") power.prop1.test(n = 31, p1 = 0.1, p0 = 0.3, power = 0.8, sig.level = NULL, alternative = "less") power.prop1.test(p1 = 0.5, p0 = 0.3, power = 0.8, alternative = "greater") power.prop1.test(p1 = 0.5, p0 = 0.3, power = 0.8, alternative = "greater", cont.corr = FALSE) power.prop1.test(n = 40, p0 = 0.3, power = 0.8, alternative = "greater") power.prop1.test(n = 40, p1 = 0.5, p0 = 0.3, power = 0.8, sig.level = NULL, alternative = "greater") ```