Package: JMbayes 0.9-0

Dimitris Rizopoulos

JMbayes: Joint Modeling of Longitudinal and Time-to-Event Data under a Bayesian Approach

Shared parameter models for the joint modeling of longitudinal and time-to-event data using MCMC; Dimitris Rizopoulos (2016) <doi:10.18637/jss.v072.i07>.

Authors:Dimitris Rizopoulos [aut, cre]

JMbayes_0.9-0.tar.gz
JMbayes_0.9-0.zip(r-4.7-x86_64)JMbayes_0.9-0.zip(r-4.7-arm64)JMbayes_0.9-0.zip(r-4.6-x86_64)JMbayes_0.9-0.zip(r-4.6-arm64)
JMbayes_0.9-0.tar.gz(r-4.7-arm64)JMbayes_0.9-0.tar.gz(r-4.7-x86_64)JMbayes_0.9-0.tar.gz(r-4.6-arm64)JMbayes_0.9-0.tar.gz(r-4.6-x86_64)
JMbayes_0.9-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
JMbayes/json (API)

# Install 'JMbayes' in R:
install.packages('JMbayes', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/drizopoulos/jmbayes/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
Datasets:
  • aids - Didanosine versus Zalcitabine in HIV Patients
  • aids.id - Didanosine versus Zalcitabine in HIV Patients
  • pbc2 - Mayo Clinic Primary Biliary Cirrhosis Data
  • pbc2.id - Mayo Clinic Primary Biliary Cirrhosis Data
  • prothro - Prednisone versus Placebo in Liver Cirrhosis Patients
  • prothros - Prednisone versus Placebo in Liver Cirrhosis Patients

On CRAN:

Conda:

openblascppopenmpjags

4.13 score 3 stars 90 scripts 603 downloads 17 mentions 35 exports 101 dependencies

Last updated from:35e97f47dc. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK200
linux-devel-x86_64OK261
source / vignettesOK294
linux-release-arm64OK216
linux-release-x86_64OK227
windows-devel-arm64OK336
windows-devel-x86_64OK340
windows-release-arm64OK336
windows-release-x86_64OK239
wasm-releaseOK169

Exports:anova.JMbayesaucJMbma.combinecoef.JMbayescvDCLdbsdgtdnsdynCJMdynInfoextract_lmeComponentsfind_thresholdsfixef.JMbayesibsIndvPred_lmeinsjointModelBayeslogLik.JMbayesmarglogLikmvglmermvJointModelBayespgtplot.JMbayesplot.survfit.JMbayesprederrJMpredict_eventTimepredict.JMbayesqgtranef.JMbayesrgtrocJMrunDynPredsurvfitJMtvextable.JMbayes

Dependencies:abindbackportsbase64encBHbslibcachemcallrcheckmatecliclustercodacodetoolscolorspacecommonmarkcpp11data.tabledescdigestdistributionaldoParallelevaluatefarverfastmapfontawesomeforeachforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvinlineisobanditeratorsjagsUIjquerylibjsonliteknitrlabelinglaterlatticelifecycleloomagrittrMASSMatrixmatrixStatsmemoisemimenlmennetnumDerivotelpillarpkgbuildpkgconfigposteriorprocessxpromisespsQuickJSRR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrjagsrlangrmarkdownrpartrstanrstudioapiS7sassscalesshinysourcetoolsStanHeadersstringistringrsurvivaltensorAtibbletinytexutf8vctrsviridisLitewithrxfunxtableyaml

Readme and manuals

Help Manual

Help pageTopics
Didanosine versus Zalcitabine in HIV Patientsaids aids.id
Anova Method for Fitted Joint Modelsanova.JMbayes
Time-Dependent ROCs and AUCs for Joint ModelsaucJM aucJM.JMbayes aucJM.mvJMbayes find_thresholds find_thresholds.mvJMbayes predict_eventTime predict_eventTime.mvJMbayes rocJM rocJM.JMbayes rocJM.mvJMbayes
Combines Predictions for Bayesian Model Averagingbma.combine
Estimated Coefficients and Confidence Intervals for Joint Modelscoef.JMbayes confint.JMbayes fixef.JMbayes
Dynamic InformationcvDCL
Derivatives and Integrals of B-splines and Natural Cubic splinesdbs dns ibs ins
A Dynamic Discrimination Index for Joint ModelsdynCJM dynCJM.JMbayes
Dynamic Information of an Extra Longitudinal MeasurementdynInfo
Fitted Values and Residuals for Joint Modelsfitted.JMbayes residuals.JMbayes
The Generalized Student's t Distributiondgt pgt qgt rgt
Individualized Predictions from Linear Mixed Modelsextract_lmeComponents IndvPred_lme
Joint Modeling of Longitudinal and Time-to-Event Data in R under a Bayesian ApproachJMbayes-package JMbayes
Fitted JMbayes ObjectJMbayesObject
Joint Models for Longitudinal and Time-to-Event DatajointModelBayes
Log-Likelihood for Joint ModelslogLik.JMbayes
Calculates Marginal Subject-specific Log-Likelihood ContributionsmarglogLik
Multivariate Mixed Modelsmvglmer
Multivariate Joint Models for Longitudinal and Time-to-Event DatamvJointModelBayes
Mayo Clinic Primary Biliary Cirrhosis Datapbc2 pbc2.id
MCMC Diagnostics for Joint Modelsplot.JMbayes
Plot Method for survfit.JMbayes and survfit.mvJMbayes Objectsplot.survfit.JMbayes plot.survfit.mvJMbayes
Prediction Errors for Joint ModelsprederrJM prederrJM.JMbayes prederrJM.mvJMbayes
Predictions for Joint Modelspredict.JMbayes
Prednisone versus Placebo in Liver Cirrhosis Patientsprothro prothros
Random Effects Estimates for Joint Modelsranef.JMbayes
Shiny Application for Dynamic PredictionsrunDynPred
Prediction in Joint ModelssurvfitJM survfitJM.JMbayes survfitJM.mvJMbayes
Time-Varying Effects using P-splinestve
xtable Method from Joint Models.xtable.JMbayes