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-4.7-any)wec_0.4-1.zip(r-4.6-any)wec_0.4-1.zip(r-4.5-any)
wec_0.4-1.tgz(r-4.6-any)wec_0.4-1.tgz(r-4.5-any)
wec_0.4-1.tar.gz(r-4.7-any)wec_0.4-1.tar.gz(r-4.6-any)
wec_0.4-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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 from:64f2cead36. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 100 | ||
| source / vignettes | OK | 143 | ||
| linux-release | OK | 103 | ||
| macos-release | OK | 172 | ||
| macos-oldrel | OK | 164 | ||
| windows-devel | OK | 77 | ||
| windows-release | OK | 54 | ||
| windows-oldrel | OK | 67 | ||
| wasm-release | OK | 85 |
Exports:contr.wecwec.interact
Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr
