Package index
-
Mods()getResp()plotMods()plot(<Mods>) - Define dose-response models
-
guesst() - Calculate guesstimates based on prior knowledge
-
optContr()plot(<optContr>)plotContr() - Calculate optimal contrasts
-
optDesign()calcCrit()rndDesign()plot(<DRdesign>) - Function to calculate optimal designs
-
planMod()summary(<planMod>)plot(<planMod>) - Evaluate performance metrics for fitting dose-response models
-
powMCT() - Calculate power for multiple contrast test
-
sampSize()sampSizeMCT()targN()powN()plot(<targN>) - Sample size calculations
-
DesignMCPModApp() - Start externally hosted DesignMCPMod Shiny App
-
MCPMod()predict(<MCPMod>)plot(<MCPMod>) - MCPMod - Multiple Comparisons and Modeling
-
MCTpval() - Calculate multiplicity adjusted p-values for multiple contrast test
-
MCTtest() - Performs multiple contrast test
-
bMCTtest() - Performs Bayesian multiple contrast test
-
powMCTInterim() - Calculate Conditional or Predictive Power for Multiple Contrast Test
-
critVal() - Calculate critical value for multiple contrast test
-
mvpostmix() - Prior to posterior updating for a multivariate normal mixture
-
mvtnorm.control() - Control options for pmvt and qmvt functions
-
bFitMod()coef(<bFitMod>)predict(<bFitMod>)plot(<bFitMod>) - Fit a dose-response model using Bayesian or bootstrap methods.
-
defBnds() - Calculates default bounds for non-linear parameters in dose-response models
-
emax()emaxGrad()sigEmax()sigEmaxGrad()exponential()exponentialGrad()quadratic()quadraticGrad()betaMod()betaModGrad()linear()linearGrad()linlog()linlogGrad()logistic()logisticGrad()linInt()linIntGrad() - Built-in dose-response models in DoseFinding
-
fitMod()coef(<DRMod>)vcov(<DRMod>)predict(<DRMod>)plot(<DRMod>)logLik(<DRMod>)AIC(<DRMod>)gAIC(<DRMod>) - Fit non-linear dose-response model
-
maFitMod()predict(<maFit>)plot(<maFit>) - Fit dose-response models via bootstrap model averaging (bagging)