gov.sandia.cognition.statistics.method

Class NemenyiConfidence.Statistic

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic

All Implemented Interfaces:

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

Enclosing class:

NemenyiConfidence

public static class NemenyiConfidence.Statistic
extends AbstractMultipleHypothesisComparison.Statistic

Statistic from Nemenyi's multiple comparison test

See Also:

Serialized Form

Field Summary

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

nullHypothesisProbabilities, testStatistics, treatmentCount, uncompensatedAlpha

Constructor Summary

Constructors

Constructor and Description
Statistic(double uncompensatedAlpha, int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans, double standardError) 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) .
NemenyiConfidence.Statistic	clone() This makes public the clone method on the Object class and removes the exception that it throws.
protected Matrix	computeNullHypothesisProbabilities(int subjectCount, Matrix Z) Computes null-hypothesis probability for the (i,j) treatment comparison
Matrix	computeTestStatistics(int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans, double standardError) Computes the test statistic for all treatments
double	getStandardError() Getter for standardError
int	getSubjectCount() Getter for subjectCount
java.util.ArrayList<java.lang.Double>	getTreatmentMeans() Getter for treatmentRankMeans

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

Constructor Detail

Statistic

public Statistic(double uncompensatedAlpha,
                 int subjectCount,
                 java.util.ArrayList<java.lang.Double> treatmentRankMeans,
                 double standardError)

Creates a new instance of StudentizedMultipleComparisonStatistic

Parameters:

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

subjectCount - Number of subjects in each treatment

treatmentRankMeans - Mean for each treatment

standardError - Standard error of the entire experiment

Method Detail

computeTestStatistics

public Matrix computeTestStatistics(int subjectCount,
                                    java.util.ArrayList<java.lang.Double> treatmentRankMeans,
                                    double standardError)

Computes the test statistic for all treatments

Parameters:

subjectCount - Number of subjects in each treatment

treatmentRankMeans - Mean for each treatment

standardError - Standard error of the entire experiment

Returns:

Test statistics, where the (i,j) element compares treatment "i" to treatment "j", the statistic is symmetric

computeNullHypothesisProbabilities

protected Matrix computeNullHypothesisProbabilities(int subjectCount,
                                                    Matrix Z)

Computes null-hypothesis probability for the (i,j) treatment comparison

Parameters:

subjectCount - Number of subjects in the experiment

Z - Test statistic for the (i,j) treatment comparison

Returns:

Null-hypothesis probability for the (i,j) treatment comparison

clone

public NemenyiConfidence.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.

getSubjectCount

public int getSubjectCount()

Getter for subjectCount

Returns:

Number of subjects in the experiment

getStandardError

public double getStandardError()

Getter for standardError

Returns:

Standard error of the entire experiment

getTreatmentMeans

public java.util.ArrayList<java.lang.Double> getTreatmentMeans()

Getter for treatmentRankMeans

Returns:

Mean for each treatment

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