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To install, load, and use pwrss in R:
install.packages("pwrss")
library(pwrss)
Alternatively calculations can be performed using links below:
| Language | User Interface |
|---|---|
| English | https://pwrss.shinyapps.io/index/ |
| English | https://pwrss.shinyapps.io/lang-en/ |
| Turkish | https://pwrss.shinyapps.io/lang-tr/ |
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.(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/
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.