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

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 <[e-mail]> 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.

See Also

power.anova.test

Examples

## 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.