Package: wec 0.4-1
wec: Weighted Effect Coding
Provides functions to create factor variables with contrasts based on weighted effect coding, and their interactions. In weighted effect coding the estimates from a first order regression model show the deviations per group from the sample mean. This is especially useful when a researcher has no directional hypotheses and uses a sample from a population in which the number of observation per group is different.
Authors:
wec_0.4-1.tar.gz
wec_0.4-1.zip(r-4.5)wec_0.4-1.zip(r-4.4)wec_0.4-1.zip(r-4.3)
wec_0.4-1.tgz(r-4.4-any)wec_0.4-1.tgz(r-4.3-any)
wec_0.4-1.tar.gz(r-4.5-noble)wec_0.4-1.tar.gz(r-4.4-noble)
wec_0.4-1.tgz(r-4.4-emscripten)wec_0.4-1.tgz(r-4.3-emscripten)
wec.pdf |wec.html✨
wec/json (API)
| # Install 'wec' in R: |
| install.packages('wec', repos = c('https://rensenieuwenhuis.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:64f2cead36. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-win | OK | Nov 13 2024 |
| R-4.5-linux | OK | Nov 13 2024 |
| R-4.4-win | OK | Nov 13 2024 |
| R-4.4-mac | OK | Nov 13 2024 |
| R-4.3-win | OK | Nov 13 2024 |
| R-4.3-mac | OK | Nov 13 2024 |
Exports:contr.wecwec.interact
Dependencies:clidplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr
