Adaptive Optimal Two-Stage Designs

Vignettes

- README.md
- Composite Scores"
- Conditional Scores and Constraints"
- Defining New Scores"
- Get started with adoptr"
- The adoptr Package: Adaptive Optimal Designs for Clinical Trials in R"
- Working with priors"

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**adoptr:**Adaptive Optimal Two-Stage Designs**AverageN2-class:**Regularization via L1 norm**BinomialDataDistribution-class:**Binomial data distribution**boundary-designs:**Boundary designs**bounds:**Get support of a prior or data distribution**composite:**Score Composition**condition:**Condition a prior on an interval**ConditionalPower-class:**(Conditional) Power of a Design**ConditionalSampleSize-class:**(Conditional) Sample Size of a Design**Constraints:**Formulating Constraints**ContinuousPrior-class:**Continuous univariate prior distributions**critical-values:**Query critical values of a design**cumulative_distribution_function:**Cumulative distribution function**DataDistribution-class:**Data distributions**expectation:**Expected value of a function**get_initial_design:**Initial design**GroupSequentialDesign-class:**Group-sequential two-stage designs**make_tunable:**Fix parameters during optimization**MaximumSampleSize-class:**Maximum Sample Size of a Design**minimize:**Find optimal two-stage design by constraint minimization**n:**Query sample size of a design**N1-class:**Regularize n1**NormalDataDistribution-class:**Normal data distribution**OneStageDesign-class:**One-stage designs**plot-TwoStageDesign-method:**Plot 'TwoStageDesign' with optional set of conditional scores**PointMassPrior-class:**Univariate discrete point mass priors**posterior:**Compute posterior distribution**predictive_cdf:**Predictive CDF**predictive_pdf:**Predictive PDF**print.adoptrOptimizationResult:**Printing an optimization result**Prior-class:**Univariate prior on model parameter**probability_density_function:**Probability density function**Scores:**Scores**simulate-TwoStageDesign-numeric-method:**Draw samples from a two-stage design**StudentDataDistribution-class:**Student's t data distribution**subject_to:**Create a collection of constraints**tunable_parameters:**Switch between numeric and S4 class representation of a...**TwoStageDesign-class:**Two-stage designs**Browse all...**

print.adoptrOptimizationResult | R Documentation |

Printing an optimization result

```
print(x, ...)
```

`x` |
object to print |

`...` |
further arguments passed form other methods |

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