R: Basic Functions for Power Analysis pwr

pwr-package {pwr} | R Documentation

## Basic Functions for Power Analysis pwr

### Description

Power calculations along the lines of Cohen (1988) using in particular the same notations for effect sizes. Examples from the book are given.

### Details

Package: | pwr
Type: | Package
Version: | 1.2-2
Date: | 2018-03-03
License: | GPL (>= 3)

This package contains functions for basic power calculations using effect sizes and notations from Cohen (1988) : pwr.p.test: test for one proportion (ES=h) pwr.2p.test: test for two proportions (ES=h) pwr.2p2n.test: test for two proportions (ES=h, unequal sample sizes) pwr.t.test: one sample and two samples (equal sizes) t tests for means (ES=d) pwr.t2n.test: two samples (different sizes) t test for means (ES=d) pwr.anova.test: test for one-way balanced anova (ES=f) pwr.r.test: correlation test (ES=r) pwr.chisq.test: chi-squared test (ES=w) pwr.f2.test: test for the general linear model (ES=f2) ES.h: computing effect size h for proportions tests ES.w1: computing effect size w for the goodness of fit chi-squared test ES.w2: computing effect size w for the association chi-squared test cohen.ES: computing effect sizes for all the previous tests corresponding to conventional effect sizes (small, medium, large)

### Author(s)

Stephane Champely, based on previous works by Claus Ekstrom and Peter Dalgaard, with contributions of Jeffrey Gill, Stephan Weibelzahl, Clay Ford, Aditya Anandkumar and Robert Volcic.

Maintainer: Helios De Rosario-Martinez <helios.derosario@gmail.com>

### References

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

### See Also

power.t.test,power.prop.test,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 6.1 p. 198 from Cohen (1988)
    pwr.2p.test(h=0.3,n=80,sig.level=0.05,alternative="greater")

    ## Exercise 7.3 p. 251
    pwr.chisq.test(w=0.346,df=(2-1)*(3-1),N=140,sig.level=0.01)

    ## Exercise 6.5 p. 203 from Cohen (1988)
    pwr.p.test(h=0.2,n=60,sig.level=0.05,alternative="two.sided")

[Package pwr version 1.2-2 Index]