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::: {} To install, load, and use pwrss in R: install.packages("pwrss") library(pwrss)

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::: {} Alternatively calculations can be performed using links below:

LanguageUser Interface
Englishhttps://pwrss.shinyapps.io/index/
Englishhttps://pwrss.shinyapps.io/lang-en/
Turkishhttps://pwrss.shinyapps.io/lang-tr/

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pwrss R package allows statistical power and minimum required sample size calculations for

  • (1) testing a proportion (one-sample) against a constant,
  • (2) testing a mean (one-sample) against a constant,
  • (3) testing difference between two proportions (independent samples),
  • (4) testing difference between two means/groups (parametric and non-parametric tests for independent and paired samples),
  • (5) testing a correlation (one-sample) against a constant,
  • (6) testing difference between two correlations (independent samples),
  • (7) testing a coefficient (with standardized or unstandardized coefficients, with no covariates or covariate adjusted) in multiple linear regression, logistic regression, and Poisson regression,
  • (8) testing an indirect effect (with standardized or unstandardized coefficients, with no covariates or covariate adjusted) in the mediation analysis (Sobel, Joint, and Monte Carlo),
  • (9) testing an R-squared against zero in linear regression
  • (10) testing an R-squared difference against zero in hierarchical regression
  • (11) testing an eta-squared or f-squared (for main and interaction effects) against zero in analysis of variance (ANOVA) (could be one-way, two-way, and three-way),
  • (12) testing an eta-squared or f-squared (for main and interaction effects) against zero in analysis of covariance (ANCOVA) (could be one-way, two-way, and three-way),
  • (13) testing an eta-squared or f-squared (for between, within, and interaction effects) against zero in one-way repeated measures analysis of variance (RM-ANOVA) (with non-sphericity correction and repeated measures correlation),
  • (14) testing goodness-of-fit or independence for contingency tables.

Alternative hypothesis can be formulated as "not equal", "less", "greater", "non-inferior", "superior", or "equivalent" in (1), (2), (3), and (4); as "not equal", "less", or "greater" in (5), (6), (7) and (8); but always as "greater" in (9), (10), (11), (12), (13) and (14).

If you find the package and related material useful please cite as:

  • Bulus, M. (2023). pwrss: Statistical Power and Sample Size Calculation Tools. R package version 0.3.1. https://CRAN.R-project.org/package=pwrss

  • Bulus, M., & Polat, C. (in press). pwrss R paketi ile istatistiksel guc analizi [Statistical power analysis with pwrss R package]. Ahi Evran Universitesi Kirsehir Egitim Fakultesi Dergisi. https://osf.io/ua5fc/download/

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Version

Install

install.packages('pwrss')

Monthly Downloads

1,934

Version

0.3.1

License

GPL (>= 3)

Maintainer

Metin Bulus

Last Published

April 11th, 2023

Functions in pwrss (0.3.1)

pwrss.t.2means

Difference between Two Means (t or z Test for Independent or Paired Samples)
power.z.test

Statistical Power for the Generic z Test
pwrss.t.mean

One Mean against a Constant (z or t Test)
pwrss.z.corr

One Correlation against a Constant (One Sample z Test)
pwrss.z.prop

One Proportion against a Constant (z Test)
power.t.test

Statistical Power for the Generic t Test
pwrss.np.2groups

Difference between Two Groups (Non-parametric Tests for Independent and Paired Samples)
pwrss.z.2corrs

Difference between Two Correlations (Independent Samples z Test)
power.f.test

Statistical Power for the Generic F Test
power.chisq.test

Statistical Power for the Generic Chi-square Test
pwrss.f.ancova

Analysis of (Co)Variance (F test)
pwrss.z.logreg

Logistic Regression: Single Coefficient (Large Sample Approx. Wald's z Test)
plot

Type I and Type II Error Plot
pwrss.chisq.gofit

Goodness-of-Fit or Independence (Chi-square Test)
pwrss.f.rmanova

Repeated Measures Analysis of Variance (F test)
pwrss.z.2props

Difference between Two Proportions (z Test)
pwrss.z.poisreg

Poisson Regression: Single Coefficient (Large Sample Approx. Wald's z Test)
pwrss.t.reg

Linear Regression: Single Coefficient (t or z Test)
pwrss.f.reg

Linear Regression: R-squared or R-squared Difference (F Test)
pwrss.z.med

Indirect Effect in Mediation Analysis (z, Joint, and Monte Carlo Tests)