Package edu.cmu.tetrad.search.test

Class ChiSquareTest

java.lang.Object
edu.cmu.tetrad.search.test.ChiSquareTest
public class ChiSquareTest extends Object
Calculates chi-square or g-square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi-square and degrees of freedom for each conditional table in turn, where rows or columns that sum to less than a given threshold have been removed. The adjusted conditional tables are required to have more than 0 total counts and at least 2 rows and 2 columns; otherwise, the test is judged to be invalid. Otherwise, a p-value is returned based on the Chi-Square distribution with the total degrees of freedom and total chi-square.
Version:
$Id: $Id
Author:
frankwimberly, josephramsey
See Also:

  • Nested Class Summary

    Nested Classes
    Modifier and Type
    Class
    Description
    static class 
    ChiSquareTest.Result
    Simple class to store the parameters of the result returned by the G Square test.
    static enum 
    ChiSquareTest.TestType
    The type of test to perform.

  • Constructor Summary

    Constructors
    Constructor
    Description
    ChiSquareTest(DataSet dataSet, double alpha, ChiSquareTest.TestType testType)
    Constructs a test using the given data set and significance level.

  • Method Summary

    Modifier and Type
    Method
    Description
    ChiSquareTest.Result
    calcChiSquare(int[] testIndices)
    Calculates chi square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi square and degrees of freedom for each conditional table in turn, where rows or columns that with fewer than minSumRowOrCol counts have been removed.
    double
    getAlpha()
    Returns the model significance level being used for tests.
    boolean
    isDetermined(int[] testIndices, double p)
    Returns a judgment of whether a set of parent variables determines a child variables.
    void
    setAlpha(double alpha)
    Sets the significance level to be used for tests.
    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 in the data.

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • ChiSquareTest

      public ChiSquareTest(DataSet dataSet, double alpha, ChiSquareTest.TestType testType)
      Constructs a test using the given data set and significance level.
      Parameters:
      dataSet - A data set consisting entirely of discrete variables.
      alpha - The significance level, usually 0.05.
      testType - The type of test to perform, either CHI_SQUARE or G_SQUARE.

  • Method Details

    • calcChiSquare

      public ChiSquareTest.Result calcChiSquare(int[] testIndices)
      Calculates chi square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi square and degrees of freedom for each conditional table in turn, where rows or columns that with fewer than minSumRowOrCol counts have been removed. The adjusted conditional tables are required to have more than 0 total counts and at least 2 rows and 2 columns; otherwise, the test is judged to be invalid. Otherwise, a p-value is returned based on the Chi-Square distribution with the total degrees of freedom and total chi-square.
      Parameters:
      testIndices - These indices, in order.
      Returns:
      a Chi square test result.
      See Also:

    • isDetermined

      public boolean isDetermined(int[] testIndices, double p)
      Returns a judgment of whether a set of parent variables determines a child variables.
      Parameters:
      testIndices - An array of indices for variables in the dataset supplied in the constructor.
      p - The probability that some marginal for some table dominates. A good value is 0.99.
      Returns:
      True if the variable at index 0 is determined by the variables at the other indices.

    • getAlpha

      public double getAlpha()
      Returns the model significance level being used for tests.
      Returns:
      this level.

    • setAlpha

      public void setAlpha(double alpha)
      Sets the significance level to be used for tests.
      Parameters:
      alpha - This significance level.

    • setRows

      public void setRows(List<Integer> rows)
      Sets the rows to use in the data.
      Parameters:
      rows - The rows to use.

    • 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.