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easypower  

Sample Size Estimation for Experimental Designs
View on CRAN: Click here


Download and install easypower package within the R console
Install from CRAN:
install.packages("easypower")

Install from Github:
library("remotes")
install_github("cran/easypower")

Install by package version:
library("remotes")
install_version("easypower", "1.0.2")



Attach the package and use:
library("easypower")
Maintained by
Aaron McGarvey
[Scholar Profile | Author Map]
First Published: 2015-11-06
Latest Update: 2015-11-06
Description:
Power analysis is used in the estimation of sample sizes for experimental designs. Most programs and R packages will only output the highest recommended sample size to the user. Often the user input can be complicated and computing multiple power analyses for different treatment comparisons can be time consuming. This package simplifies the user input and allows the user to view all of the sample size recommendations or just the ones they want to see. The calculations used to calculate the recommended sample sizes are from the 'pwr' package.
How to cite:
Aaron McGarvey (2015). easypower: Sample Size Estimation for Experimental Designs. R package version 1.0.2, https://cran.r-project.org/web/packages/easypower. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0.1 (2015-11-06 05:49)
Other packages that cited easypower R package
View easypower citation profile
Other R packages that easypower depends, imports, suggests or enhances
Complete documentation for easypower
Functions, R codes and Examples using the easypower R package
Some associated functions: easypower . n.multiway . n.oneway . 
Some associated R codes: easypower.R . f2_functions.R . n_multiway.R . n_oneway.R . names_levels_df.R . power_calculations.R . print_output_functions.R .  Full easypower package functions and examples
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