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) <doi:10.1214/21-EJS1802> and Koner and Luo (2023) <doi:10.48550/arXiv.2302.05612> respectively.">

fPASS: Power and Sample Size for Projection Test under Repeated Measures (original) (raw)

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) <doi:10.1214/21-EJS1802> and Koner and Luo (2023) <doi:10.48550/arXiv.2302.05612> respectively.

Version: 1.0.0
Imports: dplyr, purrr, face, magrittr, MASS, Matrix, nlme, testthat, mgcv, lifecycle, expm, gamm4, gss, rlang, stringr, utils
Suggests: knitr, rmarkdown, Hotelling, refund, foreach
Published: 2023-07-19
DOI: 10.32614/CRAN.package.fPASS
Author: Salil Koner ORCID iD [aut, cre, cph], Sheng Luo [ctb, fnd]
Maintainer: Salil Koner <salil.koner at duke.edu>
BugReports: https://github.com/SalilKoner/fPASS/issues
License: MIT + file
URL: https://github.com/SalilKoner/fPASS
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: fPASS results

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