Libraries.Compute.Statistics.Reporting.CompareCountsResult Documentation

This class represents data that comes back from a CompareCounts calculation (chi-squared test).

Inherits from: Libraries.Language.Object, Libraries.Compute.Statistics.Reporting.StatisticalTestResult

Actions Documentation

Compare(Libraries.Language.Object object)

This action compares two object hash codes and returns an integer. The result is larger if this hash code is larger than the object passed as a parameter, smaller, or equal. In this case, -1 means smaller, 0 means equal, and 1 means larger. This action was changed in Quorum 7 to return an integer, instead of a CompareResult object, because the previous implementation was causing efficiency issues.

Parameters

Return

integer: The Compare result, Smaller, Equal, or Larger.

Example

Object o
Object t
integer result = o:Compare(t) //1 (larger), 0 (equal), or -1 (smaller)

Equals(Libraries.Language.Object object)

This action determines if two objects are equal based on their hash code values.

Parameters

Return

boolean: True if the hash codes are equal and false if they are not equal.

Example

use Libraries.Language.Object
use Libraries.Language.Types.Text
Object o
Text t
boolean result = o:Equals(t)

GetAdjustedResiduals()

Obtains the adjusted residuals dataframe calculated by the test.

Return

Libraries.Compute.Statistics.DataFrame: the residual values in a dataframe.

GetApproximationWarningFlag()

Obtains the warning flag set by the test.

Return

boolean: the warning flag boolean.

GetCriticalValue()

This indicates the critical value for any statistical test that was run

Return

number: the critical value

GetDegreesOfFreedom()

The degrees of freedom (if only one) calculated for this result.

Return

number:

GetDegreesOfFreedomTable(text source)

The hash table of df-values for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetDegreesOfFreedomTable()

The full double hash table of df-values

Return

Libraries.Containers.HashTable:

GetEffectSize()

The effect size (if only one) calculated for this result.

Return

number:

GetEffectSizeName()

The effect size name (if only one) calculated for this result.

Return

text:

GetEffectSizesTable()

The full double hash table of effect sizes

Return

Libraries.Containers.HashTable:

GetEffectSizesTable(text source)

The hash table of effect sizes for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetExpected()

Obtains the expected dataframe calculated by the test.

Return

Libraries.Compute.Statistics.DataFrame: the expected values in a dataframe.

GetExperimentalDesign()

Return

Libraries.Compute.Statistics.Tests.ExperimentalDesign

GetFormalNumericalResult()

P-value > α: Cannot conclude that the variables are associated (Fail to reject H0)

Return

text:

GetFormalSummary()

This action summarizes the result and places it into formal academic language, in APA format. For more information: https://apastyle.apa.org/instructional-aids/numbers-statistics-guide.pdf

Return

text:

GetFormalTestName()

Returns the name of the test in formal mathematical language.

Return

text: the name of the test in mathematical language.

GetFormat()

Returns true if this result is significant against the significance level

Return

Libraries.Compute.Statistics.Reporting.StatisticsFormatting:

GetGroupsFrame()

The effect size (if only one) calculated for this result.

Return

Libraries.Compute.Statistics.DataFrame:

GetGroupsTable()

The full double hash table of stat-values

Return

Libraries.Containers.HashTable:

GetHashCode()

This action gets the hash code for an object.

Return

integer: The integer hash code of the object.

Example

Object o
integer hash = o:GetHashCode()

GetInformation()

The full double hash table of effect sizes

Return

Libraries.Containers.HashTable:

GetMatrixInformation()

The hash table of effect sizes for this source, could have one or more

Return

Libraries.Containers.HashTable:

GetObserved()

Obtains the observed dataframe calculated by the test.

Return

Libraries.Compute.Statistics.DataFrame: the observed values in a dataframe.

GetPairwiseResults()

Saved results for pairwise post hoc test (if conducted)

Return

Libraries.Containers.Array:

GetPairwiseSummary()

Returns the summary of a CompareCountsPairwise test in CompareCounts (if conducted)

Return

text:

GetPairwiseTest()

Saved test for pairwise post hoc test (if conducted)

Return

Libraries.Compute.Statistics.Tests.CompareCountsPairwise:

GetProbabilityValue()

The p-value (if only one) calculated for this result.

Return

number:

GetProbabilityValuesTable()

The full double hash table of p-values

Return

Libraries.Containers.HashTable:

GetProbabilityValuesTable(text source)

The hash table of p-values for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetReportDiv()

add the meta-data character set

Return

Libraries.Web.Page.Division:

GetReportResult(Libraries.System.File file)

This creates an HTML page with the results as its contents.

Parameters

GetResiduals()

Obtains the pearson residuals dataframe calculated by the test.

Return

Libraries.Compute.Statistics.DataFrame: the residual values in a dataframe.

GetSampleSize()

Obtains the sample size for the test.

Return

integer: the sample size.

GetSignificanceLevel()

Obtains the significance level.

Return

number: the significance level.

GetSources()

The pairwise results of each sub-sample tests within the post hoc test (if conducted)

Return

Libraries.Containers.Array:

GetSummary()

This action summarizes the result and lists it informally. It does not list the observed, expected or residual dataframes as those can be very large. If those are wanted, it's best to get them separately.

Return

text:

GetTestStatistic()

The test statistic (if only one) calculated for this result.

Return

number:

GetTestStatisticName()

The test statistic name (if only one) calculated for this result.

Return

text:

GetTestStatisticsTable()

The full double hash table of stat-values

Return

Libraries.Containers.HashTable:

GetTestStatisticsTable(text source)

The hash table of test statistics for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

IsRepeated()

The hash table of test statistics for this source, could have one or more

Return

boolean:

IsSignificant()

Returns true if this result is significant against the significance level

Return

boolean:

Repeated(boolean repeated)

The test statistic (if only one) calculated for this result.

Parameters

  • boolean repeated

SetAdjustedResiduals(Libraries.Compute.Statistics.DataFrame adjustedResiduals)

Sets the adjusted residuals dataframe calculated by the test.

Parameters

SetApproximationWarningFlag(boolean flag)

Sets the warning flag for the test.

Parameters

  • boolean flag

SetCriticalValue(number criticalValue)

This sets the critical value for any statistical test that was run

Parameters

  • number criticalValue

SetDegreesOfFreedom(text source, text dfName, number dfValue)

Stores the degrees of freedom for each group or test statistic, some may have multiple dfs calculated Examples: SetInformation("A", "between", 4) SetInformation("A", "within", 2)

Parameters

  • text source
  • text dfName
  • number dfValue

SetDegreesOfFreedom(number degreesOfFreedom)

Sets the degrees of freedom value (df in statistics) calculated by the test.

Parameters

  • number degreesOfFreedom: the degrees of freedom

SetEffectSize(number effectSize)

Sets the effect size used for this test.

Parameters

  • number effectSize: is the effect size used for this test.

SetEffectSize(text source, text effectName, number effectSize)

Stores the effect size for each group, some groups may have multiple effect sizes calculated Examples: SetInformation("A", "Cohen's D", 1.2) SetInformation("A", "Eta-Squared", 0.52)

Parameters

  • text source
  • text effectName
  • number effectSize

SetEffectSizeName(text effectSizeName)

Sets the name of the effect size used for this test.

Parameters

  • text effectSizeName: is the name of the effect size used for this test.

SetExpected(Libraries.Compute.Statistics.DataFrame expected)

Sets the expected dataframe calculated by the test.

Parameters

SetExperimentalDesign(Libraries.Compute.Statistics.Tests.ExperimentalDesign design)

Parameters

SetFactor(text factor)

Sets the factor (if used) used in this calculation.

Parameters

  • text factor

SetFormalTestName(text formalTestName)

Sets the name of the test in formal mathematical language.

Parameters

  • text formalTestName: the name of the test in mathematical language.

SetFormat(Libraries.Compute.Statistics.Reporting.StatisticsFormatting format)

Sets the significance level of the test (default is 0.05).

Parameters

SetGoodnessOfFit(boolean goodnessOfFit)

Sets the goodness of fit flag for the test.

Parameters

  • boolean goodnessOfFit: is true if the result comes from a goodness of fit test.

SetGroupsFrame(Libraries.Compute.Statistics.DataFrame groupsFrame)

The effect size name (if only one) calculated for this result.

Parameters

SetGroupsTable(Libraries.Containers.HashTable<text:Libraries.Compute.Statistics.DataFrame> groupsTable)

Stores the effect size for each group, some groups may have multiple effect sizes calculated Examples: SetInformation("A", "Cohen's D", 1.2) SetInformation("A", "Eta-Squared", 0.52)

Parameters

SetInformation(text source, text infoName, number infoValue)

Stores the other information for each group, could include summary values, sum of squares etc Examples: SetInformation("A", "Mean", 10) SetInformation("A", "Sum Of Squares", 32.45)

Parameters

  • text source
  • text infoName
  • number infoValue

SetInformation(text source, text infoName, Libraries.Compute.Matrix infoValue)

Stores the other information for each group, could include summary values, sum of squares etc Examples: SetInformation("A", "Mean", 10) SetInformation("A", "Sum Of Squares", 32.45)

Parameters

SetObserved(Libraries.Compute.Statistics.DataFrame observed)

Sets the observed dataframe calculated by the test.

Parameters

SetPairwiseResults(Libraries.Containers.Array<Libraries.Compute.Statistics.Reporting.CompareCountsResult> pairwise)

Saved results for pairwise post hoc test (if conducted)

Parameters

SetPairwiseTest(Libraries.Compute.Statistics.Tests.CompareCountsPairwise test)

Saved test for pairwise post hoc test (if conducted)

Parameters

SetProbabilityValue(number probabilityValue)

Sets the probability value (p in statistics) calculated by the test.

Parameters

  • number probabilityValue: the probability

SetProbabilityValue(text source, text statistic, number probabilityValue)

Stores the p-value for each group and test statistic Example: SetInformation("A", "t", 0.05)

Parameters

  • text source
  • text statistic
  • number probabilityValue

SetResiduals(Libraries.Compute.Statistics.DataFrame residuals)

Sets the residuals dataframe calculated by the test.

Parameters

SetSampleSize(integer sampleSize)

Sets the sample size for the test.

Parameters

  • integer sampleSize: is sample size.

SetSignificanceLevel(number significanceLevel)

Sets the significance level of the test (default is 0.05).

Parameters

  • number significanceLevel: the significance level between 0 and 1.

SetSources(Libraries.Containers.Array<text> sources)

The pairwise test which holds more easily accessible results especially with factorial design

Parameters

SetTestStatistic(number testStatistic)

This sets the calculated test statistic for any statistical test that was run

Parameters

  • number testStatistic

SetTestStatistic(text source, text statName, number testStatistic)

Stores the test statistic for each group, some groups may have multiple test statistics calculated Examples: SetInformation("A", "T", 1.34) SetInformation("A", "Wilk's Lambda", 1.39)

Parameters

  • text source
  • text statName
  • number testStatistic

SetVariable1(text variable)

Sets the first column (or only column) used in this calculation.

Parameters

  • text variable: is column header.

SetVariable2(text variable)

Sets the second column (if used) used in this calculation.

Parameters

  • text variable: is column header.