# pwr.anova.test: Power calculations for balanced one-way analysis of variance... In pwr: Basic Functions for Power Analysis

## Description

Compute power of test or determine parameters to obtain target power (same as power.anova.test).

## Usage

 `1` ```pwr.anova.test(k = NULL, n = NULL, f = NULL, sig.level = 0.05, power = NULL) ```

## Arguments

 `k` Number of groups `n` Number of observations (per group) `f` Effect size `sig.level` Significance level (Type I error probability) `power` Power of test (1 minus Type II error probability)

## Details

Exactly one of the parameters 'k','n','f','power' and 'sig.level' must be passed as NULL, and that parameter is determined from the others. Notice that the last one has non-NULL default so NULL must be explicitly passed if you want to compute it.

## Value

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

## Note

'uniroot' is used to solve power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

## Author(s)

Stephane Champely <champely@univ-lyon1.fr> but this is a mere copy of Peter Dalgaard work (power.t.test)

## References

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale,NJ: Lawrence Erlbaum.

power.anova.test

## Examples

 ```1 2 3 4 5``` ```## Exercise 8.1 P. 357 from Cohen (1988) pwr.anova.test(f=0.28,k=4,n=20,sig.level=0.05) ## Exercise 8.10 p. 391 pwr.anova.test(f=0.28,k=4,power=0.80,sig.level=0.05) ```

### Example output

```     Balanced one-way analysis of variance power calculation

k = 4
n = 20
f = 0.28
sig.level = 0.05
power = 0.5149793

NOTE: n is number in each group

Balanced one-way analysis of variance power calculation

k = 4
n = 35.75789
f = 0.28
sig.level = 0.05
power = 0.8

NOTE: n is number in each group
```

pwr documentation built on March 17, 2020, 5:11 p.m.