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

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic
          extended by gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic
All Implemented Interfaces:
MultipleHypothesisComparison.Statistic, CloneableSerializable, Serializable, 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
protected  ArrayList<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
AbstractPairwiseMultipleHypothesisComparison.Statistic(Collection<? extends Collection<? extends Number>> data, double uncompensatedAlpha, NullHypothesisEvaluator<Collection<? extends Number>> pairwiseTest)
          Creates a new instance of StudentizedMultipleComparisonStatistic
 
Method Summary
 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(Collection<? extends Collection<? extends Number>> data, NullHypothesisEvaluator<Collection<? extends 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
 ArrayList<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 ArrayList<ArrayList<ConfidenceStatistic>> pairwiseTestStatistics
Results from the pair-wise confidence tests.

Constructor Detail

AbstractPairwiseMultipleHypothesisComparison.Statistic

public AbstractPairwiseMultipleHypothesisComparison.Statistic(Collection<? extends Collection<? extends Number>> data,
                                                              double uncompensatedAlpha,
                                                              NullHypothesisEvaluator<Collection<? extends 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(Collection<? extends Collection<? extends Number>> data,
                                          NullHypothesisEvaluator<Collection<? extends 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 ArrayList<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