Package: crctStepdown 0.5.2
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-4.5-noble)crctStepdown_0.5.2.tar.gz(r-4.4-noble)
crctStepdown_0.5.2.tgz(r-4.4-emscripten)crctStepdown_0.5.2.tgz(r-4.3-emscripten)
crctStepdown.pdf |crctStepdown.html✨
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 10 months agofrom:134a0f14b1. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 29 2024 |
R-4.5-linux-x86_64 | OK | Nov 29 2024 |
Exports:est_null_modelgen_rand_orderoutname_fitsetParallelCRTsimpleLMstepdowntwoarm_sim
Dependencies:abindbackportsBHbigmemorybigmemory.sribootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverfastglmFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompurrrquantregR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8uuidvctrsviridisLitewithr
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 |