Package: NRejections 1.2.0
NRejections: Metrics for Multiple Testing with Correlated Outcomes
Implements methods in Mathur and VanderWeele (in preparation) to characterize global evidence strength across W correlated ordinary least squares (OLS) hypothesis tests. Specifically, uses resampling to estimate a null interval for the total number of rejections in, for example, 95% of samples generated with no associations (the global null), the excess hits (the difference between the observed number of rejections and the upper limit of the null interval), and a test of the global null based on the number of rejections.
Authors:
NRejections_1.2.0.tar.gz
NRejections_1.2.0.zip(r-4.7)NRejections_1.2.0.zip(r-4.6)NRejections_1.2.0.zip(r-4.5)
NRejections_1.2.0.tgz(r-4.6-any)NRejections_1.2.0.tgz(r-4.5-any)
NRejections_1.2.0.tar.gz(r-4.7-any)NRejections_1.2.0.tar.gz(r-4.6-any)
NRejections_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NRejections/json (API)
| # Install 'NRejections' in R: |
| install.packages('NRejections', repos = c('https://mayamathur.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:86a425e9a2. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 117 | ||
| source / vignettes | OK | 170 | ||
| linux-release-x86_64 | OK | 103 | ||
| macos-release-arm64 | OK | 87 | ||
| macos-oldrel-arm64 | OK | 75 | ||
| windows-devel | OK | 95 | ||
| windows-release | OK | 65 | ||
| windows-oldrel | OK | 73 | ||
| wasm-release | OK | 93 |
Exports:adj_minPadj_Wstepcell_corrcorr_testsdataset_resultfit_modelfix_inputget_critmake_corr_matresample_residsim_data
Dependencies:codetoolsdoParallelforeachiteratorsmatrixcalcmvtnormRcppRcppArmadilloStepwiseTest
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adjust p-values using minP | adj_minP |
| Return Wstep-adjusted p-values | adj_Wstep |
| Cell correlation for simulating data | cell_corr |
| Global evidence strength across correlated tests | corr_tests |
| Fit all models for a single dataset | dataset_result |
| Fit OLS model for a single outcome | fit_model |
| Fix bad user input | fix_input |
| Return ordered critical values for Wstep | get_crit |
| Makes correlation matrix to simulate data | make_corr_mat |
| Resample residuals for OLS | resample_resid |
| Simulate MVN data | sim_data |
