The pwr4exp
R package provides functions for power
calculation and sample size determination in standard experimental
designs in animal science and beyond. The package emphasizes the
importance of specifying models for conducting power analyses and
supports power analyses for main effects, interactions, and specific
contrasts. Additionally, pwr4exp
offers a flexible
framework to perform power analysis on customized designs which are
currently not predefined in the package.
# You can install pwr4exp from CRAN
install.packages("pwr4exp")
# Or the the development version from GitHub:
# install.packages("devtools")
::install_github("an-ethz/pwr4exp") devtools
Performing power analysis in pwr4exp
involves the
following steps: - First, create a design object using the design
generating functions. - Once the design object is created, calculating
power or determining sample size using pwr4exp
is
straightforward. Simply pass the design object to the power calculator
for main effects and interactions, pwr.anova()
, or for
contrasts, pwr.contrast()
. - To determine the minimal
sample size to achieve a target power, a quoted design object can be
passed to the function find_sample_size()
.
Here’s an example of how you can generate a design and calculate power:
library(pwr4exp)
# Create a design
<- designRCBD(
rcbd treatments = c(2, 2),
blocks = 10,
beta = c(470, 30, -55, 5),
VarCov = 3200,
sigma2 = 3200
)# Calculate power for the ominubus test (i.e., F-test)
pwr.anova(design = rcbd)
# Calculate power for specific contrasts
pwr.contrast(design = rcbd, specs = ~ facB | facA, contrast = "pairwise")
To learn more about pwr4exp
, read through the vignette
for pwr4exp
which contains:
pwr4exp
to assess the power of
customized designs.The documentation for this package is being updated. If you have any questions or suggestions, please feel free to contact the package maintainer.