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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) <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 |
| Author: |
Salil Koner  [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 LICENSE |
| URL: |
https://github.com/SalilKoner/fPASS |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
fPASS results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
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