Estimation in Optimal Adaptive Two-Stage Designs
adestr
Normal prior distribution for the parameter mu
Analyze a dataset
Combine EstimatoreScoreResult objects into a list
Combine EstimatoreScoreResult objects into a list
Calculate the second-stage critical value for a design with cached spl...
Performance scores for point and interval estimators
Evaluate performance characteristics of an estimator
Evaluate performance characteristics of an estimator
Evaluate different scenarios in parallel
Generate an exemplary adaptive design
Generate a list of estimators and p-values to use in examples
Conditional representations of an estimator or p-value
Generate the list of estimators and p-values that were used in the pap...
Interval estimators
Calculate the second-stage sample size for a design with cached spline...
Plot p-values and implied rejection boundaries
Plot performance scores for point and interval estimators
Plot performance scores for point and interval estimators
Plot performance scores for point and interval estimators
Point estimators
P-values
Statistics and Estimators of the adestr package
TwoStageDesignWithCache constructor function
Uniform prior distribution for the parameter mu
Methods to evaluate the performance characteristics of various point and interval estimators for optimal adaptive two-stage designs as described in Meis et al. (2024) <doi:10.1002/sim.10020>. Specifically, this package is written to work with trial designs created by the 'adoptr' package (Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09>; Pilz et al. (2021) <doi:10.1002/sim.8953>)). Apart from the a priori evaluation of performance characteristics, this package also allows for the evaluation of the implemented estimators on real datasets, and it implements methods to calculate p-values.