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.

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/