ES.w1: Effect size calculation in the chi-squared test for goodness...

In pwr: Basic Functions for Power Analysis

Description

Compute effect size w for two sets of k probabilities P0 (null hypothesis) and P1 (alternative hypothesis)

Usage

ES.w1(P0, P1)

Arguments

P0	First set of k probabilities (null hypothesis)
P1	Second set of k probabilities (alternative hypothesis)

Value

The corresponding effect size w

Author(s)

Stephane CHAMPELY

References

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

See Also

pwr.chisq.test

Examples

## Exercise 7.1 p. 249 from Cohen 
P0<-rep(1/4,4)
P1<-c(0.375,rep((1-0.375)/3,3))
ES.w1(P0,P1)
pwr.chisq.test(w=ES.w1(P0,P1),N=100,df=(4-1))

Example output

[1] 0.2886751

     Chi squared power calculation 

              w = 0.2886751
              N = 100
             df = 3
      sig.level = 0.05
          power = 0.6739834

NOTE: N is the number of observations

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