fPASS
Power and Sample Size for Projection Test under Repeated Measures
Computes the power and sample size (PASS) required to test for the
difference in the mean function between two groups under a repeatedly measured longitudinal
or sparse functional design. See the manuscript by Koner and Luo (2023) < https://salilkoner.github.io/assets/PASS_manuscript.pdf>
for details of the PASS formula and computational details. The details of the testing
procedure for univariate and multivariate response are presented in
Wang (2021)
fPASS: Power and Sample Size Analysis for Projection-Based Testing of Mean Difference under Repeated Measures Design
The details of the power and sample size formula and the relevant computational details are documented in the manuscript. The users are encourage to see Wang (2021) and Koner and Luo (2023) for further details about the testing procedure.
fPASS is designed to make it quick and easy software for randomized clinical trial simulation tool for determining treatment efficacy where the response collected under a longitudinal or functional design. The current development version of the package can be installed by running the following.
Installation
# Install development version from GitHub
devtools::install_github("SalilKoner/fPASS") # Vignettes takes about 20 minutes to run.
Vignettes
If you want to install the package with the vignettes to be built, then run
# Install development version from GitHub with the vignettes.
# Vignettes takes about 5-7 minutes to run.
devtools::install_github("SalilKoner/fPASS", build_vignettes = TRUE)
followed by browseVignettes("fPASS") to see the application of the
package in real life case studies.