Package: prome 1.9.1.0
Bin Wang
prome: Patient-Reported Outcome Data Analysis with Stan
Algorithms and subroutines for patient-reported outcome data analysis.
Authors:
prome_1.9.1.0.tar.gz
prome_1.9.1.0.tar.gz(r-4.5-noble)prome_1.9.1.0.tar.gz(r-4.4-noble)
prome.pdf |prome.html✨
prome/json (API)
| # Install 'prome' in R: |
| install.packages('prome', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- ex100x3 - Sample PRO Data With Repeated Measures
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:e0cc444ac3. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 26 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 26 2024 |
Exports:bateMeanHMpratioPropHMResponderAnalysisxover
Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The 'prome' package. | prome-package prome |
| Bayesian Hierarchical Model for RPO data with repeated measures | bate plot.memix pratio print.memix ResponderAnalysis |
| Sample PRO Data With Repeated Measures | ex100x3 n100x3 |
| Bayesian Hierarchical Model for Information Borrowing for Means | MeanHM |
| Bayesian Hierarchical Model for Information Borrowing for Proportions | PropHM |
| Bayesian analysis of 2x2 crossover trial data | print.xover xover |