# power.anova.test

0th

Percentile

##### Power Calculations for Balanced One-Way Analysis of Variance Tests

Compute power of test or determine parameters to obtain target power.

Keywords
htest
##### Usage
power.anova.test(groups = NULL, n = NULL,
between.var = NULL, within.var = NULL,
sig.level = 0.05, power = NULL)
##### Arguments
groups

Number of groups

n

Number of observations (per group)

between.var

Between group variance

within.var

Within group variance

sig.level

Significance level (Type I error probability)

power

Power of test (1 minus Type II error probability)

##### Details

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

##### 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.

anova, lm, uniroot
library(stats) # NOT RUN { power.anova.test(groups = 4, n = 5, between.var = 1, within.var = 3) # Power = 0.3535594 power.anova.test(groups = 4, between.var = 1, within.var = 3, power = .80) # n = 11.92613 ## Assume we have prior knowledge of the group means: groupmeans <- c(120, 130, 140, 150) power.anova.test(groups = length(groupmeans), between.var = var(groupmeans), within.var = 500, power = .90) # n = 15.18834 # }