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