Package: JMbdirect 0.1.0
JMbdirect: Joint Model for Longitudinal and Multiple Time to Events Data
Provides model fitting, prediction, and plotting for joint models of longitudinal and multiple time-to-event data, including methods from Rizopoulos (2012) <doi:10.1201/b12208>. Useful for handling complex survival and longitudinal data in clinical research.
Authors:
JMbdirect_0.1.0.tar.gz
JMbdirect_0.1.0.zip(r-4.5)JMbdirect_0.1.0.zip(r-4.4)JMbdirect_0.1.0.zip(r-4.3)
JMbdirect_0.1.0.tgz(r-4.5-any)JMbdirect_0.1.0.tgz(r-4.4-any)JMbdirect_0.1.0.tgz(r-4.3-any)
JMbdirect_0.1.0.tar.gz(r-4.5-noble)JMbdirect_0.1.0.tar.gz(r-4.4-noble)
JMbdirect_0.1.0.tgz(r-4.4-emscripten)JMbdirect_0.1.0.tgz(r-4.3-emscripten)
JMbdirect.pdf |JMbdirect.html✨
JMbdirect/json (API)
| # Install 'JMbdirect' in R: |
| install.packages('JMbdirect', repos = c('https://atanubhattacharjee.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 21 days agofrom:b24e8e5e8f. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 12 2025 |
| R-4.5-win | OK | Mar 12 2025 |
| R-4.5-mac | OK | Mar 12 2025 |
| R-4.5-linux | OK | Mar 12 2025 |
| R-4.4-win | OK | Mar 12 2025 |
| R-4.4-mac | OK | Mar 12 2025 |
| R-4.4-linux | OK | Mar 12 2025 |
| R-4.3-win | OK | Mar 12 2025 |
| R-4.3-mac | OK | Mar 12 2025 |
Exports:bootciJMCSjmbBjmcsBjmrmlBjmstB
Dependencies:abindbackportsbase64encbayesplotBHbootbslibcachemcallrcaretcheckmateclasscliclockclustercmprskcobscodacodetoolscolorspacecolourpickercommonmarkcpp11crayoncrosstalkdata.tabledescdiagramdigestdistributionaldoParalleldplyrDTdygraphse1071evaluatefansifarverFastJMfastmapfontawesomeforeachforeignFormulafsfuturefuture.applygenericsggplot2ggridgesGLMMadaptiveglobalsgluegowergridExtragtablegtoolshardhathighrHmischtmlTablehtmltoolshtmlwidgetshttpuvigraphinlineipredisobanditeratorsJMbayes2jmBIGjoineRMLjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlme4loolubridatemagrittrmarkdownMASSMatrixMatrixModelsmatrixStatsmemoisemetsmgcvmimeminiUIminqaModelMetricsmultcompmunsellmvtnormnlmenloptrnnetnumDerivparallellypecpillarpkgbuildpkgconfigplotrixplyrpolsplineposteriorpROCprocessxprodlimprogressrpromisesproxypsPublishpurrrquantregQuickJSRR6randtoolboxrangerrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackrecipesreformulasreshape2riskRegressionrlangrmarkdownrmsrngWELLrpartrstanrstanarmrstantoolsrstudioapisandwichsassscalesshapeshinyshinyjsshinystanshinythemessourcetoolsSparseMsparsevctrsSQUAREMStanHeadersstatmodstringistringrsurvivaltensorATH.datathreejstibbletidyrtidyselecttimechangetimeDatetimeregtimeROCtinytextzdbutf8vctrsviridisviridisLitewithrxfunxtablextsyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Function for bootstrapped confidence interval | bootciJMCS |
| Joint model for Bidirectional survival data using 'JMbayes2' | jmbB |
| Joint model for Bidirectional survival data using 'FastJM' | jmcsB |
| Joint model for Bidirectional survival data using 'joineRML' | jmrmlB |
| Joint model for Bidirectional survival data using 'rstanarm' | jmstB |
| longitudinal- survival dataset | new_long2 |
| survival data | new_surv2 |
| Prediction plot from 'jmbB()' | plot.jmbB |
| Prediction plot from 'jmcsB()' | plot.jmcsB |
| Prediction plot from 'jmrmlB()' | plot.jmrmlB |
| Prediction plot from 'jmstB()' | plot.jmstB |
| predict.jmbB | predict.jmbB |
| predict.jmcsB | predict.jmcsB |
| predict.jmrmlB | predict.jmrmlB |
| predict.jmstB | predict.jmstB |
| print. | print.jmbB |
| print. | print.jmcsB |
| print. | print.jmrmlB |
| print. | print.jmstB |
