Package edu.cmu.tetrad.search.test

Class IndTestChiSquare

java.lang.Object

edu.cmu.tetrad.search.test.IndTestChiSquare

All Implemented Interfaces:

EffectiveSampleSizeSettable, IndependenceTest, RowsSettable

public final class IndTestChiSquare
extends Object
implements IndependenceTest, EffectiveSampleSizeSettable, RowsSettable

Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional Chi Square test. A description of such a test is given in Fienberg, "The Analysis of Cross-Classified Categorical Data," 2nd edition. The formulas for the degrees of freedom used in this test are equivalent to the formulation on page 142 of Fienberg.

Version:

$Id: $Id

Author:

josephramsey

See Also:

• ChiSquareTest

Constructor Summary

Constructors

Constructor	Description
IndTestChiSquare(DataSet dataSet, double alpha)	Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Determines whether variable x is independent of variable y given a list of conditioning varNames z.
boolean	determines(List<Node> z, Node x)	Determines whether variable x is independent of variable y given a list of conditioning nodes.
boolean	determines(Set<Node> _z, Node x)	Determines whether variable x is independent of a set of variables _z.
double	getAlpha()	Returns the alpha significance level of the test.
double	getChiSquare()	Returns the chi Square value.
DataSet	getData()	Returns the data being analyzed.
int	getDf()	Returns the degrees of freedom associated with the most recent call of isIndependent.
Double	getPValue(Node x, Node y, Set<Node> z)	Returns the pvalue if the fact of X _||_ Y | Z is within the cache of results for independence fact.
List<Integer>	getRows()	Returns the rows used for the test.
List<Node>	getVariables()	Returns the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
IndependenceTest	indTestSubset(List<Node> nodes)	Checks conditional independence between variables in a subset.
boolean	isVerbose()	Checks if the verbosity flag is enabled.
void	setAlpha(double alpha)	Sets the significance level at which independence judgments should be made.
void	setCellTableType(ChiSquareTest.CellTableType cellTableType)	Sets the cell table type.
void	setDeterminationP(double determinationP)	Sets the threshold for making judgments of determination.
void	setEffectiveSampleSize(int sampleSize)	Sets the sample size if the sample size of the data or covariance matrix is not the sample size that should be used by the class.
void	setMinCountPerCell(double minCountPerCell)	The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom.
void	setRows(List<Integer> rows)	Sets the rows to use for the test.
void	setVerbose(boolean verbose)	Sets whether verbose output should be printed.
String	toString()	Returns a string representation of this test.

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.cmu.tetrad.search.IndependenceTest

checkIndependence, getCov, getDataSets, getSampleSize, getVariable, getVariableNames

Constructor Details

IndTestChiSquare

public IndTestChiSquare(DataSet dataSet,
 double alpha)

Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.

Parameters:

dataSet - the discrete data set.

alpha - the significance level of the tests.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> nodes)

Checks conditional independence between variables in a subset.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

nodes - The sublist of variables.

Returns:

An instance of IndependenceTest representing the test for conditional independence.

Throws:

IllegalArgumentException - If the subset of variables is empty or contains non-original nodes.

getChiSquare

public double getChiSquare()

Returns the chi Square value.

Returns:

This value.

getDf

public int getDf()

Returns the degrees of freedom associated with the most recent call of isIndependent.

Returns:

These degrees.

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 Set<Node> _z)

Determines whether variable x is independent of variable y given a list of conditioning varNames z.

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

x - a Node object

y - a Node object

_z - a Set object

Returns:

a IndependenceResult object

See Also:

• IndependenceResult

getPValue

public Double getPValue(Node x,
 Node y,
 Set<Node> z)

Returns the pvalue if the fact of X _||_ Y | Z is within the cache of results for independence fact.

Parameters:

x - the first node

y - the second node

z - the set of conditioning nodes

Returns:

the pValue result or null if not within the cache

determines

public boolean determines(List<Node> z,
 Node x)

Determines whether variable x is independent of variable y given a list of conditioning nodes.

Parameters:

z - The list of conditioning nodes.

x - The variable x.

Returns:

True if variable x is determined by the list of conditioning nodes, false otherwise.

Throws:

NullPointerException - if z or any node in z is null.

IllegalArgumentException - if any node in z is not used in the constructor.

getAlpha

public double getAlpha()

Returns the alpha significance level of the test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

This level.

setAlpha

public void setAlpha(double alpha)

Sets the significance level at which independence judgments should be made. Affects the cutoff for partial correlations to be considered statistically equal to zero.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - This level.

getVariables

public List<Node> getVariables()

Returns the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.

Specified by:

getVariables in interface IndependenceTest

Returns:

This list.

toString

public String toString()

Returns a string representation of this test.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

This string.

getData

public DataSet getData()

Returns the data being analyzed.

Specified by:

getData in interface IndependenceTest

Returns:

This data.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

isVerbose

public boolean isVerbose()

Checks if the verbosity flag is enabled.

Specified by:

isVerbose in interface IndependenceTest

Returns:

true if the verbosity flag is enabled, false otherwise

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.

setMinCountPerCell

public void setMinCountPerCell(double minCountPerCell)

The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom. Note that this should not be too small, or the chi-square distribution will not be a good approximation to the distribution of the test statistic.

Parameters:

minCountPerCell - The minimum number of counts per conditional table. The default is 1; this must be >= 0.

getRows

public List<Integer> getRows()

Returns the rows used for the test. If null, all rows are used.

Specified by:

getRows in interface RowsSettable

Returns:

The rows to use for the test. Can be null.

setRows

public void setRows(List<Integer> rows)

Sets the rows to use for the test. If null, all rows are used.

Specified by:

setRows in interface RowsSettable

Parameters:

rows - The rows to use for the test. Can be null.

setEffectiveSampleSize

public void setEffectiveSampleSize(int sampleSize)

Description copied from interface: EffectiveSampleSizeSettable

Sets the sample size if the sample size of the data or covariance matrix is not the sample size that should be used by the class.

Specified by:

setEffectiveSampleSize in interface EffectiveSampleSizeSettable

Parameters:

sampleSize - The sample size to use.

setCellTableType

public void setCellTableType(ChiSquareTest.CellTableType cellTableType)

Sets the cell table type.

Parameters:

cellTableType - The cell table type.

setDeterminationP

public void setDeterminationP(double determinationP)

Sets the threshold for making judgments of determination.

Parameters:

determinationP - This threshold.

determines

public boolean determines(Set<Node> _z,
 Node x)

Determines whether variable x is independent of a set of variables _z.

Specified by:

determines in interface IndependenceTest

Parameters:

_z - a set of variables to condition on

x - the variable to check for independence

Returns:

true if variable x is independent of _z, false otherwise

Throws:

NullPointerException - if _z or any element in _z is null

IllegalArgumentException - if any variable in _z or x was not used in the constructor