Package: interactionTest 1.2
Justin Esarey
interactionTest: Calculates Critical Test Statistics to Control False Discovery Rates in Marginal Effects Plots
Implements the procedures suggested in Esarey and Sumner (2017) <http://justinesarey.com/interaction-overconfidence.pdf> for controlling the false discovery rate when constructing marginal effects plots for models with interaction terms.
Authors:
interactionTest_1.2.tar.gz
interactionTest_1.2.tar.gz(r-4.5-noble)interactionTest_1.2.tar.gz(r-4.4-noble)
interactionTest_1.2.tgz(r-4.4-emscripten)interactionTest_1.2.tgz(r-4.3-emscripten)
interactionTest.pdf |interactionTest.html✨
interactionTest/json (API)
| # Install 'interactionTest' in R: |
| install.packages('interactionTest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- legfig - Replication data for Clark and Golder
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:85dbdf104d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 19 2024 |
| R-4.5-linux | OK | Dec 19 2024 |
Exports:bootFunfdrInteractionfindMultiLims
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bootstrapping t-statistics | bootFun |
| Critical t-statistic | fdrInteraction |
| Determine Critical t-Statistic For Marginal Effects Plot | findMultiLims |
| Replication data for Clark and Golder (2006) | legfig |