@ConfidenceTestAssumptions(name="Sidak correction",alsoKnownAs="Dunn-Sidak correction",description={"Sidak\'s correction is a conservative way to compensate for pair-wise null-hypothesis comparisons applied to multiple comparison to control false-discovery rate.","The correction is known to be overly conservative, trading low false-discovery for high false-negative rates.","The Sidak correction is tighter than the Bonferroni correction, and the Sidak correction is generally preferred."},assumptions={"The assumptions of the underlying pair-wise test are met.","The treatments must be independent."},nullHypothesis="Each treatment has no effect on the measurements of the subjects",dataPaired=true,dataSameSize=true,distribution=AbstractClosedFormSmoothUnivariateDistribution.class,reference={@PublicationReference(author="Janez Demsar",title="Statistical Comparisons of Classifiers over Multiple Data Sets",type=Journal,publication="Journal of Machine Learning Research",year=2006,url="http://www.jmlr.org/papers/volume7/demsar06a/demsar06a.pdf"),@PublicationReference(author="Wikipedia",title="Bonferroni Correction",type=WebPage,year=2011,url="http://en.wikipedia.org/wiki/Bonferroni_correction")}) public class SidakCorrection extends AbstractPairwiseMultipleHypothesisComparison<AdjustedPValueStatistic>
AbstractPairwiseMultipleHypothesisComparison.StatisticDEFAULT_PAIRWISE_TEST, pairwiseTestDEFAULT_UNCOMPENSATED_ALPHA| Constructor and Description |
|---|
SidakCorrection()
Creates a new instance of SidakCorrection
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SidakCorrection(NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest)
Creates a new instance of SidakCorrection
|
| Modifier and Type | Method and Description |
|---|---|
static double |
adjust(double uncompensatedAlpha,
int numComparisons)
Computes the Sidak multiple-comparison correction
|
SidakCorrection |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
AdjustedPValueStatistic |
evaluateNullHypotheses(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data,
double uncompensatedAlpha)
Evaluates the null hypotheses associated with the given collection
of data.
|
getPairwiseTest, setPairwiseTestevaluateNullHypothesespublic SidakCorrection()
public SidakCorrection(NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest)
pairwiseTest - Confidence test used for pair-wise null-hypothesis tests.public SidakCorrection clone()
AbstractCloneableSerializableObject class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone() to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone() as the basis for your implementation.clone in interface CloneableSerializableclone in class AbstractPairwiseMultipleHypothesisComparison<AdjustedPValueStatistic>public AdjustedPValueStatistic evaluateNullHypotheses(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data, double uncompensatedAlpha)
MultipleHypothesisComparisonevaluateNullHypotheses in interface MultipleHypothesisComparison<java.util.Collection<? extends java.lang.Number>>evaluateNullHypotheses in class AbstractMultipleHypothesisComparison<java.util.Collection<? extends java.lang.Number>,AdjustedPValueStatistic>data - Data from each treatment to consideruncompensatedAlpha - Uncompensated alpha (p-value threshold) for the multiple comparison
test, must be [0,1]public static double adjust(double uncompensatedAlpha,
int numComparisons)
uncompensatedAlpha - Uncompensated alpha (p-value threshold) for the multiple comparison
test, must be [0,1]numComparisons - Number of comparisons to make.