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:
Cloneable, CloneableSerializable, Serializable
All Known Implementing Classes:
AbstractMultipleHypothesisComparison, AbstractPairwiseMultipleHypothesisComparison, BonferroniCorrection, HolmCorrection, MultipleComparisonExperiment, NemenyiConfidence, ShafferStaticCorrection, SidakCorrection, TukeyKramerConfidence

@PublicationReferences(references={@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
static interface MultipleHypothesisComparison.Statistic
          Statistic associated with the multiple hypothesis comparison
 
Field Summary
static double DEFAULT_UNCOMPENSATED_ALPHA
          Default uncompensatedAlpha, 0.05.
 
Method Summary
 MultipleHypothesisComparison.Statistic evaluateNullHypotheses(Collection<? extends TreatmentData> data)
          Evaluates the null hypotheses associated with the given collection of data.
 MultipleHypothesisComparison.Statistic evaluateNullHypotheses(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(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(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