\name{pwr-package}
\alias{pwr-package}
\alias{pwr}
\docType{package}
\title{
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{
\tabular{ll}{
Package: \tab pwr\cr
Type: \tab Package\cr
Version: \tab 1.2-2\cr
Date: \tab 2018-03-03\cr
License: \tab GPL (>= 3) \cr
}
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{
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.}
\keyword{ package }
\keyword{htest}
\seealso{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")
}
