Package: crctStepdown 0.5.2
Sam Watson
crctStepdown: Univariate Analysis of Cluster Trials with Multiple Outcomes
Frequentist statistical inference for cluster randomised trials with multiple outcomes that controls the family-wise error rate and provides nominal coverage of confidence sets. A full description of the methods can be found in Watson et al. (2023) <doi:10.1002/sim.9831>.
Authors:
crctStepdown_0.5.2.tar.gz
crctStepdown_0.5.2.tar.gz(r-4.7-arm64)crctStepdown_0.5.2.tar.gz(r-4.7-x86_64)crctStepdown_0.5.2.tar.gz(r-4.6-arm64)crctStepdown_0.5.2.tar.gz(r-4.6-x86_64)
crctStepdown_0.5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
crctStepdown/json (API)
| # Install 'crctStepdown' in R: |
| install.packages('crctStepdown', repos = c('https://cran.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:134a0f14b1. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 217 | ||
| linux-devel-x86_64 | OK | 200 | ||
| source / vignettes | OK | 250 | ||
| linux-release-arm64 | OK | 213 | ||
| linux-release-x86_64 | OK | 203 | ||
| wasm-release | OK | 165 |
Exports:est_null_modelgen_rand_orderoutname_fitsetParallelCRTsimpleLMstepdowntwoarm_sim
Dependencies:abindbackportsBHbigmemorybigmemory.sribootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverfastglmforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreformulasreshape2rlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8uuidvctrsviridisLitewithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence interval search procedure | confint_search |
| Estimates null model | est_null_model |
| Function to generate a stepped-wedge cRCT randomisation allocation | gen_rand_order |
| Extracts the dependent variable name from glm, lm, or mer model | outname_fit |
| Extracts the test statistics | perm_dist |
| Generates realisations of the permutational test statistic distribution | permutation_test_impl |
| The quasi-score statistic for a generalised linear mixed model | qscore_impl |
| Disable or enable parallelised computing | setParallelCRT |
| A very basic linear model solver | simpleLM |
| Conduct the randomisation-based stepdown procedure | stepdown |
| Simulates data from a two-arm parallel cluster randomised trial | twoarm_sim |
