pwr: Basic functions for power analysis

Stephane Champely (Developer), Claus Ekstrom (Developer), Peter Dalgaard (Developer), Jeffrey Gill (Developer), Stephan Weibelzahl (Developer), Aditya Anandkumar (Developer), Clay Ford (Developer), Robert Volcic (Developer), Helios De Rosario (Developer)

Psychology

Research output: Non-textual form › Software

Abstract

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 fort he 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).

Original language	English (US)
Media of output	Online
State	Published - 2017

Keywords

R
Power analysis

Access to Document

https://cran.r-project.org/web/packages/pwr/License: Other

Cite this

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title = "pwr: Basic functions for power analysis",

abstract = "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 fort he 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).",

keywords = "R, Power analysis",

author = "Stephane Champely and Claus Ekstrom and Peter Dalgaard and Jeffrey Gill and Stephan Weibelzahl and Aditya Anandkumar and Clay Ford and Robert Volcic and {De Rosario}, Helios",

year = "2017",

language = "English (US)",

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T1 - pwr: Basic functions for power analysis

A2 - Champely, Stephane

A2 - Ekstrom, Claus

A2 - Dalgaard, Peter

A2 - Gill, Jeffrey

A2 - Weibelzahl, Stephan

A2 - Anandkumar, Aditya

A2 - Ford, Clay

A2 - Volcic, Robert

A2 - De Rosario, Helios

PY - 2017

Y1 - 2017

N2 - 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 fort he 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).

AB - 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 fort he 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).

KW - R

KW - Power analysis

M3 - Software

ER -

pwr: Basic functions for power analysis

Abstract

Keywords

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