gov.sandia.cognition.statistics.method

Interface MultipleHypothesisComparison<TreatmentData>

Type Parameters:

TreatmentData - Data associated with each treatment, such as Double or Collection of Double

All Superinterfaces:

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

All Known Implementing Classes:

AbstractMultipleHypothesisComparison, AbstractPairwiseMultipleHypothesisComparison, BonferroniCorrection, HolmCorrection, MultipleComparisonExperiment, NemenyiConfidence, ShafferStaticCorrection, SidakCorrection, TukeyKramerConfidence

@PublicationReference(author="Juliet Popper Shaffer",title="Multiple Hypothesis Testing",type=Journal,year=1995,publication="Annual Review of Psychology",url="http://www.annualreviews.org/doi/pdf/10.1146/annurev.ps.46.020195.003021") @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={"Salvador Garcia","Francisco Herrera"},title="An Extension on \"Statistical Comparisons of Classi\ufb01ers over Multiple Data Sets\" for all Pairwise Comparisons",type=Journal,publication="Journal of Machine Learning Research",year=2008,url="http://150.214.190.154/publications/ficheros/2008-Garcia-JMLR.pdf") @PublicationReference(author="Wikipedia",title="Multiple comparisons",type=WebPage,year=2011,url="http://en.wikipedia.org/wiki/Multiple_comparisons")
public interface MultipleHypothesisComparison<TreatmentData>
extends CloneableSerializable

Describes the functionality of an algorithm for accepting or rejecting multiple null hypothesis at the same time. These are typically run as a post-hoc test after an ANOVA or Friedman's test. The multiple comparison tests indicate which treatments are significantly different from each other once an ANOVA or Friedman's test has indicated that there are significant differences.

Since:

3.3.0

Author:

Kevin R. Dixon

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static interface	MultipleHypothesisComparison.Statistic Statistic associated with the multiple hypothesis comparison

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_UNCOMPENSATED_ALPHA Default uncompensatedAlpha, 0.05.

Method Summary

Modifier and Type	Method and Description
MultipleHypothesisComparison.Statistic	evaluateNullHypotheses(java.util.Collection<? extends TreatmentData> data) Evaluates the null hypotheses associated with the given collection of data.
MultipleHypothesisComparison.Statistic	evaluateNullHypotheses(java.util.Collection<? extends TreatmentData> data, double uncompensatedAlpha) Evaluates the null hypotheses associated with the given collection of data.

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Field Detail

DEFAULT_UNCOMPENSATED_ALPHA

static final double DEFAULT_UNCOMPENSATED_ALPHA

Default uncompensatedAlpha, 0.05.

See Also:

Constant Field Values

Method Detail

evaluateNullHypotheses

MultipleHypothesisComparison.Statistic evaluateNullHypotheses(java.util.Collection<? extends TreatmentData> data)

Evaluates the null hypotheses associated with the given collection of data.

Parameters:

data - Data from each treatment to consider

Returns:

Statistic that summarizes the multiple comparison test

evaluateNullHypotheses

MultipleHypothesisComparison.Statistic evaluateNullHypotheses(java.util.Collection<? extends TreatmentData> data,
                                                              double uncompensatedAlpha)

Evaluates the null hypotheses associated with the given collection of data.

Parameters:

data - Data from each treatment to consider

uncompensatedAlpha - Uncompensated alpha (p-value threshold) for the multiple comparison test, must be [0,1]

Returns:

Statistic that summarizes the multiple comparison test