gov.sandia.cognition.statistics.method

Class AbstractPairwiseMultipleHypothesisComparison.Statistic

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic

gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic

All Implemented Interfaces:

MultipleHypothesisComparison.Statistic, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

AdjustedPValueStatistic, HolmCorrection.Statistic, ShafferStaticCorrection.Statistic

Enclosing class:

AbstractPairwiseMultipleHypothesisComparison<StatisticType extends AbstractPairwiseMultipleHypothesisComparison.Statistic>

public abstract static class AbstractPairwiseMultipleHypothesisComparison.Statistic
extends AbstractMultipleHypothesisComparison.Statistic

Result from a pairwise multiple-comparison statistic.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected java.util.ArrayList<java.util.ArrayList<ConfidenceStatistic>>	pairwiseTestStatistics Results from the pair-wise confidence tests.

Fields inherited from class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic

nullHypothesisProbabilities, testStatistics, treatmentCount, uncompensatedAlpha

Constructor Summary

Constructors

Constructor and Description
Statistic(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data, double uncompensatedAlpha, NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest) Creates a new instance of StudentizedMultipleComparisonStatistic

Method Summary

Modifier and Type	Method and Description
boolean	acceptNullHypothesis(int i, int j) Determines if the (i,j) null hypothesis should be accepted (true) or rejected (false) .
AbstractPairwiseMultipleHypothesisComparison.Statistic	clone() This makes public the clone method on the Object class and removes the exception that it throws.
protected void	computePairwiseTestResults(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data, NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest) Computes the pair-wise confidence test results
abstract double	getAdjustedAlpha(int i, int j) Gets the adjusted alpha (p-value threshold) for the given comparison
java.util.ArrayList<java.util.ArrayList<ConfidenceStatistic>>	getPairwiseTestStatistics() Getter for pairwiseTestStatistics

Methods inherited from class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic

getNullHypothesisProbability, getTestStatistic, getTreatmentCount, getUncompensatedAlpha, toString

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

pairwiseTestStatistics

protected java.util.ArrayList<java.util.ArrayList<ConfidenceStatistic>> pairwiseTestStatistics

Results from the pair-wise confidence tests.

Constructor Detail

Statistic

public Statistic(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data,
                 double uncompensatedAlpha,
                 NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest)

Creates a new instance of StudentizedMultipleComparisonStatistic

Parameters:

data - Data from each treatment to consider

uncompensatedAlpha - Uncompensated alpha (p-value threshold) for the multiple comparison test

pairwiseTest - Confidence test used for pair-wise null-hypothesis tests.

Method Detail

clone

public AbstractPairwiseMultipleHypothesisComparison.Statistic clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object 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.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractMultipleHypothesisComparison.Statistic

Returns:

A clone of this object.

computePairwiseTestResults

protected void computePairwiseTestResults(java.util.Collection<? extends java.util.Collection<? extends java.lang.Number>> data,
                                          NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>> pairwiseTest)

Computes the pair-wise confidence test results

Parameters:

data - Data from each treatment to consider

pairwiseTest - Confidence test used for pair-wise null-hypothesis tests.

getPairwiseTestStatistics

public java.util.ArrayList<java.util.ArrayList<ConfidenceStatistic>> getPairwiseTestStatistics()

Getter for pairwiseTestStatistics

Returns:

Results from the pair-wise confidence tests.

acceptNullHypothesis

public boolean acceptNullHypothesis(int i,
                                    int j)

Description copied from interface: MultipleHypothesisComparison.Statistic

Determines if the (i,j) null hypothesis should be accepted (true) or rejected (false) . Rejecting a null hypothesis typically means that there is a significant difference between the (i,j) treatment.

Parameters:

i - First treatment index

j - Second treatment index

Returns:

True if we accept the null hypothesis, false if we reject the null hypothesis

getAdjustedAlpha

public abstract double getAdjustedAlpha(int i,
                                        int j)

Gets the adjusted alpha (p-value threshold) for the given comparison

Parameters:

i - First treatment to compare

j - Second treatment to compare

Returns:

Adjusted alpha (p-value threshold) for the given comparison