Package: clinDR 2.5.3

clinDR: Simulation and Analysis Tools for Clinical Dose Response Modeling

Bayesian and ML Emax model fitting, graphics and simulation for clinical dose response. The summary data from the dose response meta-analyses in Thomas, Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and Thomas and Roy (2016) <doi:10.1080/19466315.2016.1256229> Wu, Banerjee, Jin, Menon, Martin, and Heatherington(2017) <doi:10.1177/0962280216684528> are included in the package. The prior distributions for the Bayesian analyses default to the posterior predictive distributions derived from these references.

Authors:Neal Thomas [aut, cre], Jing Wu [aut], Mike K. Smith [aut], Budhaditya Goswami [aut], Satrajit Roychoudhury [aut]

clinDR_2.5.3.tar.gz
clinDR_2.5.3.zip(r-4.7-any)clinDR_2.5.3.zip(r-4.6-any)clinDR_2.5.3.zip(r-4.5-any)
clinDR_2.5.3.tgz(r-4.6-any)clinDR_2.5.3.tgz(r-4.5-any)
clinDR_2.5.3.tar.gz(r-4.7-any)clinDR_2.5.3.tar.gz(r-4.6-any)
clinDR_2.5.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
clinDR/json (API)

# Install 'clinDR' in R:
install.packages('clinDR', repos = c('https://snthomas99.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • metaData - Dose response data from several published meta-analyses

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.66 score 1 stars 77 scripts 385 downloads 68 exports 92 dependencies

Last updated from:2d0a171d0c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK223
source / vignettesOK252
linux-releaseOK233
macos-releaseOK169
macos-oldrelOK131
windows-develOK174
windows-releaseOK167
windows-oldrelOK164
wasm-releaseOK176

Exports:bpchkMonoEmaxcheckMonoEmaxcoef.emaxsimcoef.emaxsimBcoef.fitEmaxcoef.fitEmaxBcompileStanModelsDRDensityPlotemaxaltemaxfunemaxPrior.controlemaxsimemaxsimBfitEmaxfitEmaxBFixedMeanmcmc.controlnllogisplot.emaxsimplot.emaxsimBplot.emaxsimBobjplot.emaxsimobjplot.fitEmaxplot.fitEmaxBplot.plotBplotBplotBdensityplotDpredict.emaxaltpredict.emaxsimpredict.emaxsimBpredict.emaxsimBobjpredict.emaxsimobjpredict.fitEmaxpredict.fitEmaxBprint.emaxPriorprint.emaxsimprint.emaxsimBprint.emaxsimBobjprint.emaxsimobjprint.fitEmaxprint.fitEmaxBprior.controlRandEmaxrandomEmaxrunSimulationsSeEmaxselEstanshowStanModelssigma.emaxsimsigma.emaxsimBsigma.fitEmaxsigma.fitEmaxBsolveDosesolveEmaxstartEmaxsummary.emaxsimsummary.emaxsimBsummary.emaxsimBobjsummary.emaxsimobjsummary.fitEmaxsummary.fitEmaxBtargetBetatargetCItargetDupdate.emaxsimobjvcov.emaxsimvcov.fitEmax

Dependencies:abindaskpassbackportsbase64encBHbslibcachemcallrcheckmateclicodetoolscommonmarkcpp11descdigestdistributionaldoParallelDoseFindingdplyrfarverfastmapfontawesomeforeachfsgenericsggplot2gluegridExtragtablehtmltoolshttpuvinlineisobanditeratorsjquerylibjsonlitelabelinglaterlatticelifecycleloomagrittrmatrixStatsmemoisemimemvtnormnumDerivofficeropensslotelpillarpkgbuildpkgconfigposteriorprocessxpromisespspurrrQuickJSRR6raggrappdirsRColorBrewerRcppRcppEigenRcppParallelrlangrstanS7sassscalesshinysourcetoolsStanHeadersstringistringrsyssystemfontstensorAtextshapingtibbletidyrtidyselectutf8uuidvctrsviridisLitewaiterwithrxml2xtablezip

Example of Bayesian Emax dose response modeling
Introduction | Step 1: Dose Response in a New RA Study | Data | Pre-specified alpha-controlled hypothesis testing: MCP-Mod Trend Test | Setting up Prior for DR analysis | Fit Bayesian Dose Response | Posterior Diagnostics | Posterior Inference | Assessing the Need For a Second Study and Its Potential Design | Step 2: Dose Response in a Second RA Study | Bayesian Emax Model fitting | Dose Selection
Rendered fromDRmodeling.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-09-21

Getting started with clinDR
Introduction | Installation | Primary clinDR functions | Dose response meta-data | Example
Rendered fromgettingStarted.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-09-21

Using a Mixture Prior for E0 in the Bayesian Emax Model
Overview | Binary Response | Deriving a Mixture Prior Using RBesT | Data | Computing a MAP Prior MCMC Sample using gMAP | Parametric Approximation Derived from the MCMC Sample | Robustification and Effective Sample Size | Fit Binary Bayesian Emax Model with Mixture Prior for E0 | Continuous Response | Parametric Approximation derived from the MCMC Sample | Bayesian Emax Model with a Mixture Prior for E0 | Simulated dose response study | Model fit using fitEmaxB | References
Rendered frommixturePrior.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-09-21

Readme and manuals

Help Manual

Help pageTopics
Bayesian and maximum likelihood Emax model fitting, graphics and simulation for clinical dose response.clinDR-package
Extract a simulation from the output of emaxsim[.emaxsim
Extract a simulation from the output of emaxsimB[.emaxsimB
Bayes posterior predictive test for Emax (monotone) model fitbpchkMonoEmax
Bayes posterior predictive test for Emax (monotone) model fitcheckMonoEmax
Extract Emax model parameter estimatescoef.emaxsim coef.emaxsimB coef.fitEmax coef.fitEmaxB
Compile 'rstan' Emax models after package 'clinDR' is installedcompileStanModels
Plot Bayes or confidence interval density contours over a grid of points (usually dose or time)DRDensityPlot
Fit 4- or 3-parameter Emax model substituting simpler curves if convergence not achieved.emaxalt
Vectorized versions of the hyperbolic and sigmoidal Emax modelsemaxfun
Set the parameters of the prior distribution for the Emax model implemented in 'fitEmaxB'.emaxPrior.control
Simulate Emax maximum likelihood estimationemaxsim
Simulate Emax Bayesian estimationemaxsimB
Solve Emax function for target valuesolveDose solveEmax
ML fit of hyperbolic or sigmoidal Emax models to continuous/binary dose response data.fitEmax
Bayesian fit of hyperbolic or sigmoidal Emax models to continuous/binary dose response data.fitEmaxB
Fixed means (proportions) random data constructor for emaxsim for continuous or binary dataFixedMean
Settings for 'restan' execution in function 'fitEmaxB'mcmc.control
Dose response data from several published meta-analysesmetaData
The negative log likelihood function for a 3- or 4- parameter Emax model on the logit scale for binary dose response.nllogis
Plot the output of emaxsimplot.emaxsim
Plot the output of emaxsimBplot.emaxsimB
Plot dose response from a data set generated by emaxsimBplot.emaxsimBobj
Plot dose response from a data set generated by emaxsimplot.emaxsimobj
Plot a Emax model and dose group means.plot.fitEmax
Plot a Emax model and dose group means.plot.fitEmaxB
Plot Bayes dose response curve and dose group meansplot.plotB
Plot Bayes dose response curve and dose group meansplotB
Density plot displaying Bayes prior or posterior dose responseplotBdensity
Basic plot of dose group meansplotD
Mean response and SE for specified doses for a simulated object output by function emaxaltpredict.emaxalt
Mean response and SE for specified doses for each replicate data set in an emaxsim objectpredict.emaxsim
Mean response and SE for each replicate data set in an emaxsimB objectpredict.emaxsimB
Mean response estimates (posterior means) and SE (posterior SD) for specified doses for a simulated emaxsimBobj objectpredict.emaxsimBobj
Mean response and SE for specified doses for a simulated emaxsimobj objectpredict.emaxsimobj
Estimated mean/proportion and confidence intervals derived from the maximum likelihood fit of a 3- or 4- parameter Emax model.predict.fitEmax
Estimated mean and posterior intervals derived from a Bayesian hyperbolic or sigmiodial Emax model.predict.fitEmaxB
Print simulation output from emaxsimprint.emaxsim
Print simulation output from emaxsimBprint.emaxsimB
Print a summary of the fitted Emax modelprint.emaxsimBobj
Print a data set generated by emaxsimprint.emaxsimobj
Print a summary of the fitted Emax modelprint.fitEmax
Print a summary of the fitted Bayesian Emax modelprint.fitEmaxB
Generate and Save Protocol/SAP Text for Emax Prior Distributionsprint.emaxPrior
Set the parameters of the prior distribution for the Emax model implemented in 'fitEmaxB'.prior.control
Random data constructor function for emaxsim creating random parameters for an Emax model for continuous or binary data.RandEmax
Random data constructor function for emaxsim(B) creating random parameters for an Emax model for continuous or binary data.randomEmax
Shiny app for function 'emaxsim(B)'runSimulations
Asymptotic SE for dose response estimates from a 3- or 4- parameter Emax modelSeEmax
Select a pre-compiled 'rstan' Emax modelselEstan
Display 'STAN' model code.showStanModels
Extract Emax model residual SD estimatessigma.emaxsim sigma.emaxsimB sigma.fitEmax sigma.fitEmaxB
Compute starting parameter values for the 3- or 4- Emax model.startEmax
Summary of output of emaxsimsummary.emaxsim
Summary of output of emaxsimBsummary.emaxsimB
Summarize Emax fit to a data set generated by emaxsimBsummary.emaxsimBobj
Summarize Emax fit to a data set generated by emaxsimsummary.emaxsimobj
Print a summary of the fitted Emax modelsummary.fitEmax
Print a summary of the fitted Bayesian Emax modelsummary.fitEmaxB
Find a scaled Beta distribution matching specified probabilitiestargetBeta
Compute the dose with confidence interval exceeding a target change from placebo for each simulated example in an emaxsim object.targetCI
Compute the MLE (and its SE) of the dose achieving a specified target improvement from placebo.targetD
Update estimation in a data set generated by emaxsimupdate.emaxsimobj
Extract Emax model variance-covariance matrix for ML estimatesvcov.emaxsim vcov.fitEmax