get_stagewise_estimators {adestr} | R Documentation |
Conditional representations of an estimator or p-value
Description
This generic determines the functional representations of point and interval estimators and p-values. The functions are returned in two parts, one part to calculate the values conditional on early futility or efficacy stops (i.e. where no second stage mean and sample size is available), and one conditional on continuation to the second stage.
Usage
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualPointEstimator,ANY'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualPValue,ANY'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualIntervalEstimator,ANY'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'PointEstimator,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'PValue,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'IntervalEstimator,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualPointEstimator,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualIntervalEstimator,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'VirtualPValue,Student'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'PointEstimator,DataDistribution'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'PValue,DataDistribution'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'IntervalEstimator,DataDistribution'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'AdaptivelyWeightedSampleMean,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MinimizePeakVariance,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'BiasReduced,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'RaoBlackwell,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'PseudoRaoBlackwell,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'RepeatedCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'LinearShiftRepeatedPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MLEOrderingPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'LikelihoodRatioOrderingPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'ScoreTestOrderingPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'StagewiseCombinationFunctionOrderingPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'NeymanPearsonOrderingPValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'NaivePValue,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'StagewiseCombinationFunctionOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MLEOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'LikelihoodRatioOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'ScoreTestOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'NeymanPearsonOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'NaiveCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature
## 'MidpointStagewiseCombinationFunctionOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MidpointMLEOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MidpointLikelihoodRatioOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MidpointScoreTestOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MidpointNeymanPearsonOrderingCI,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature
## 'MedianUnbiasedStagewiseCombinationFunctionOrdering,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MedianUnbiasedMLEOrdering,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MedianUnbiasedLikelihoodRatioOrdering,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MedianUnbiasedScoreTestOrdering,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'MedianUnbiasedNeymanPearsonOrdering,Normal'
get_stagewise_estimators(
estimator,
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
Arguments
estimator |
object of class |
data_distribution |
object of class |
use_full_twoarm_sampling_distribution |
logical indicating whether this estimator is intended to be used with the full sampling distribution in a two-armed trial. |
design |
object of class |
sigma |
assumed standard deviation. |
exact |
logical indicating usage of exact n2 function. |
Value
a list with the conditional functional representations (one for each stage where the trial might end) of the estimator or p-value.
Examples
get_stagewise_estimators(
estimator = SampleMean(),
data_distribution = Normal(FALSE),
use_full_twoarm_sampling_distribution = FALSE,
design = get_example_design(),
sigma = 1,
exact = FALSE
)