- caic() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
-
- calculatesHessianVectorProduct() - Method in enum com.itemanalysis.psychometrics.optimization.StochasticCalculateMethods
-
- call() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
-
- castToInt(double[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- Category - Class in com.itemanalysis.psychometrics.data
-
CategoryScoring defines the scores assigned to values in the data.
- Category(Object, double) - Constructor for class com.itemanalysis.psychometrics.data.Category
-
- categoryIterator() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem
-
Iterator for the catgory objects
- categoryIterator() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
Return category iterator for binary and polytomous items.
- categoryIterator() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
-
- categoryMap - Variable in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
- CategoryResponseSummary - Class in com.itemanalysis.psychometrics.measurement
-
- CategoryResponseSummary(VariableName, Object, boolean, DiscriminationType) - Constructor for class com.itemanalysis.psychometrics.measurement.CategoryResponseSummary
-
- centerText(String, int) - Method in class com.itemanalysis.psychometrics.texttable.TextTableRow
-
- CGMinimizer - Class in com.itemanalysis.psychometrics.optimization
-
Conjugate-gradientAt implementation based on the code in Numerical
Recipes in C.
- CGMinimizer() - Constructor for class com.itemanalysis.psychometrics.optimization.CGMinimizer
-
Basic constructor, use this.
- CGMinimizer(boolean) - Constructor for class com.itemanalysis.psychometrics.optimization.CGMinimizer
-
Pass in false to get per-iteration progress reports
(to stderr).
- CGMinimizer(Function) - Constructor for class com.itemanalysis.psychometrics.optimization.CGMinimizer
-
Perform minimization with monitoring.
- checkConstraints(Double) - Method in class com.itemanalysis.psychometrics.scaling.ScoreBounds
-
- checkForDroppping() - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup
-
Threshold parameters cannot be estimated if one or more categories do not have any observations.
- checkPrecisionOnly(Double) - Method in class com.itemanalysis.psychometrics.scaling.ScoreBounds
-
- chiSquare - Variable in class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
-
- chiSquare2by2(int, int, int, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
-
Find a 2x2 chi-square value.
- chlhsn_f77(int, double[][], double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
-
The chlhsn_f77 method finds
"THE L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION OF THE PERTURBED
MODEL HESSIAN MATRIX A+MU*I(WHERE MU\0 AND I IS THE IDENTITY MATRIX)
WHICH IS SAFELY POSITIVE DEFINITE.
- chlhsn_f77(int, double[][], double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
-
The chlhsn_f77 method finds
"THE L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION OF THE PERTURBED
MODEL HESSIAN MATRIX A+MU*I(WHERE MU\0 AND I IS THE IDENTITY MATRIX)
WHICH IS SAFELY POSITIVE DEFINITE.
- choldc_f77(int, double[][], double, double, double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
-
The choldc_f77 method finds
"THE PERTURBED L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION
OF A+D, WHERE D IS A NON-NEGATIVE DIAGONAL MATRIX ADDED TO A IF
NECESSARY TO ALLOW THE CHOLESKY DECOMPOSITION TO CONTINUE."
Translated by Steve Verrill, April 15, 1998.
- choldc_f77(int, double[][], double, double, double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
-
The choldc_f77 method finds
"THE PERTURBED L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION
OF A+D, WHERE D IS A NON-NEGATIVE DIAGONAL MATRIX ADDED TO A IF
NECESSARY TO ALLOW THE CHOLESKY DECOMPOSITION TO CONTINUE."
Translated by Steve Verrill, April 15, 1998.
- ClassicalItem - Class in com.itemanalysis.psychometrics.measurement
-
This is the main class for conducting a classical item analysis.
- ClassicalItem(VariableAttributes, boolean, boolean, boolean, boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.ClassicalItem
-
- ClassicalItemStatistics - Class in com.itemanalysis.psychometrics.measurement
-
- ClassicalItemStatistics(Object, boolean, boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.ClassicalItemStatistics
-
- ClassicalItemStatistics(Object, boolean, boolean, boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.ClassicalItemStatistics
-
- ClassicalItemSummary - Class in com.itemanalysis.psychometrics.measurement
-
- ClassicalItemSummary(VariableAttributes, boolean, boolean, DiscriminationType) - Constructor for class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
-
- ClassicalTestSummary - Class in com.itemanalysis.psychometrics.measurement
-
A newer and more clear version of TestSummary.java.
- ClassicalTestSummary(ArrayList<VariableAttributes>, boolean, boolean, boolean, int[]) - Constructor for class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
-
- clear() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.QNInfo
-
- clear() - Method in class com.itemanalysis.psychometrics.scaling.PercentileRank
-
- clear() - Method in class com.itemanalysis.psychometrics.statistics.StorelessDescriptiveStatistics
-
- clear() - Method in class com.itemanalysis.psychometrics.statistics.TwoWayTable
-
- clearCategory() - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
-
- clearCategory() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
- clearCategory() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
-
- clearCounts() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary
-
Resets the item counts to zero.
- clearCounts() - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup
-
Resets the category counts.
- clearResponseVector() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
-
Resets the response vector and frequency counts to zero.
- clone() - Method in class com.itemanalysis.psychometrics.histogram.Bin
-
- CmhTable - Class in com.itemanalysis.psychometrics.cmh
-
A single 2 x C table for computing Cochran-Mantel-Haenszel DIF statistics.
- CmhTable(Object, Object) - Constructor for class com.itemanalysis.psychometrics.cmh.CmhTable
-
- CmhTableRow - Class in com.itemanalysis.psychometrics.cmh
-
- CmhTableRow(Object) - Constructor for class com.itemanalysis.psychometrics.cmh.CmhTableRow
-
- CochranMantelHaenszel - Class in com.itemanalysis.psychometrics.cmh
-
See the article below for details:
Zwick, R., & Thayer, D.
- CochranMantelHaenszel(String, String, VariableAttributes, VariableAttributes, boolean) - Constructor for class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
-
- cochranMantelHaenszel() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
-
- CoefficientAlpha - Class in com.itemanalysis.psychometrics.reliability
-
Computes Coefficient alpha (aka Cronbach's alpha).
- CoefficientAlpha(CovarianceMatrix) - Constructor for class com.itemanalysis.psychometrics.reliability.CoefficientAlpha
-
Constructor for coefficient alpha.
- CoefficientAlpha(double[][]) - Constructor for class com.itemanalysis.psychometrics.reliability.CoefficientAlpha
-
- colaxpy_f77(int, double, double[][], int, int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method multiplies a constant times a portion of a column
of a matrix and adds the product to the corresponding portion
of another column of the matrix --- a portion of col2 is
replaced by the corresponding portion of a*col1 + col2.
- coldot_f77(int, double[][], int, int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method calculates the dot product of portions of two
columns of a matrix.
- colisamax_f77(int, double[][], int, int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method finds the index of the element of a portion of a
column of a matrix that has the maximum absolute value.
- colnrm2_f77(int, double[][], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method calculates the Euclidean norm of a portion of a
column of a matrix.
- colrot_f77(int, double[][], int, int, double, double) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method "applies a plane rotation."
It is a modification of the LINPACK function
DROT.
- colscal_f77(int, double, double[][], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method scales a portion of a column of a matrix by a constant.
- colswap_f77(int, double[][], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method interchanges two columns of a matrix.
- columnSum(int) - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
-
- columnThresholds - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
-
- colValuesIterator() - Method in class com.itemanalysis.psychometrics.statistics.TwoWayTable
-
- colvaxpy_f77(int, double, double[][], double[], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method multiplies a constant times a portion of a column
of a matrix x[ ][ ] and adds the product to the corresponding portion
of a vector y[ ] --- a portion of y[ ] is replaced by the corresponding
portion of ax[ ][j] + y[ ].
- colvdot_f77(int, double[][], double[], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method calculates the dot product of a portion of a
column of a matrix and the corresponding portion of a
vector.
- colvraxpy_f77(int, double, double[], double[][], int, int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
-
This method multiplies a constant times a portion of a vector y[ ]
and adds the product to the corresponding portion
of a column of a matrix x[ ][ ] --- a portion of column j of x[ ][ ]
is replaced by the corresponding
portion of ay[ ] + x[ ][j].
- com.itemanalysis.psychometrics.analysis - package com.itemanalysis.psychometrics.analysis
-
- com.itemanalysis.psychometrics.cmh - package com.itemanalysis.psychometrics.cmh
-
- com.itemanalysis.psychometrics.data - package com.itemanalysis.psychometrics.data
-
- com.itemanalysis.psychometrics.distribution - package com.itemanalysis.psychometrics.distribution
-
- com.itemanalysis.psychometrics.factoranalysis - package com.itemanalysis.psychometrics.factoranalysis
-
- com.itemanalysis.psychometrics.histogram - package com.itemanalysis.psychometrics.histogram
-
- com.itemanalysis.psychometrics.irt.equating - package com.itemanalysis.psychometrics.irt.equating
-
- com.itemanalysis.psychometrics.irt.estimation - package com.itemanalysis.psychometrics.irt.estimation
-
- com.itemanalysis.psychometrics.irt.model - package com.itemanalysis.psychometrics.irt.model
-
- com.itemanalysis.psychometrics.kernel - package com.itemanalysis.psychometrics.kernel
-
- com.itemanalysis.psychometrics.measurement - package com.itemanalysis.psychometrics.measurement
-
- com.itemanalysis.psychometrics.mixture - package com.itemanalysis.psychometrics.mixture
-
- com.itemanalysis.psychometrics.optimization - package com.itemanalysis.psychometrics.optimization
-
- com.itemanalysis.psychometrics.polycor - package com.itemanalysis.psychometrics.polycor
-
- com.itemanalysis.psychometrics.reliability - package com.itemanalysis.psychometrics.reliability
-
- com.itemanalysis.psychometrics.scaling - package com.itemanalysis.psychometrics.scaling
-
- com.itemanalysis.psychometrics.statistics - package com.itemanalysis.psychometrics.statistics
-
- com.itemanalysis.psychometrics.texttable - package com.itemanalysis.psychometrics.texttable
-
- com.itemanalysis.psychometrics.tools - package com.itemanalysis.psychometrics.tools
-
- com.itemanalysis.psychometrics.uncmin - package com.itemanalysis.psychometrics.uncmin
-
- commonOddsRatio() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
-
Computed only for the first two rows and first two columns in each strata
- commonOddsRatioConfidenceInterval(double) - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
-
Computes 95% confidence interval for the common odds ratio.
- commonOddsRatioDenominator() - Method in class com.itemanalysis.psychometrics.cmh.CmhTable
-
- commonOddsRatioNumerator() - Method in class com.itemanalysis.psychometrics.cmh.CmhTable
-
- commonOddsRatioVariance() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
-
- communality - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
-
- compare(Object, Object) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring.ItemResponseComparator
-
- compareTo(Object) - Method in class com.itemanalysis.psychometrics.data.Category
-
- compareTo(VariableAttributes) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
-
compare by item name.
- compareTo(Object) - Method in class com.itemanalysis.psychometrics.data.VariableLabel
-
- compareTo(VariableName) - Method in class com.itemanalysis.psychometrics.data.VariableName
-
- compareTo(ItemResponseVector) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
-
- compareTo(Covariance) - Method in class com.itemanalysis.psychometrics.polycor.Covariance
-
- compareTo(PearsonCorrelation) - Method in class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
-
- compareTo(ScoreReliability) - Method in class com.itemanalysis.psychometrics.reliability.AbstractScoreReliability
-
- compareTo(ConditionalSEM) - Method in class com.itemanalysis.psychometrics.reliability.ConditionalSEM
-
- compareTo(CSEM) - Method in class com.itemanalysis.psychometrics.reliability.CSEM
-
- compareTo(Object) - Method in class com.itemanalysis.psychometrics.scaling.RawScore
-
- completeDataLogLikelihood() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
-
Computes the complete data log-likelihood.
- ComponentDistribution - Interface in com.itemanalysis.psychometrics.mixture
-
- compute() - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepParallel
-
Recusive computation of the Estep for parallel processing.
- compute() - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtObservedScoreDistribution
-
Computes the IRT observed score distribution for a test that contains binary items, polytomous items, or
binary and polytomous items.
- compute() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitG2
-
- compute() - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemFitStatistic
-
- compute() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitSX2
-
- compute() - Method in class com.itemanalysis.psychometrics.irt.estimation.MstepParallel
-
Parallel processing handled here.
- computeAllBinaryItems() - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtObservedScoreDistribution
-
Computes the IRT observed score distribution for a test that contains only binary items.
- computeCategoryScore(Object, Object) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
Returns 1 if response == categoryId and 0 otherwise.
- computeCategoryScore(Object, Object) - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
-
- computeCategoryStandardError(double[], int[]) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup
-
Computes the standard error of the threshold parameters.
- computeCoefficients() - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
-
- computeCSEM(ScoreReliability, boolean) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
-
- computeCSEM(ScoreReliability, boolean) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
-
- computeDecisionConsistency() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
-
- computeDecisionConsistency() - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
-
- computeDirectly() - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepParallel
-
Estep computation when the number of response vectors is less than estepParallelThreshold or when
the recursive algorithm has reached its stopping condition.
- computeDirectly() - Method in class com.itemanalysis.psychometrics.irt.estimation.MstepParallel
-
Mstep computation when the number of items is less than the threshold or when the
stopping condition has been reached.
- computeEpsilon() - Static method in class com.itemanalysis.psychometrics.measurement.MachineAccuracy
-
compute EPSILON from scratch
- computeG2ItemFit(int, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
-
- computeItemCategoryFitStatistics() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
-
After estimation, INFIT and OUTFIT mean square fit statistics for category thresholds can be computed.
- computeItemFitStatistics() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
-
After parameters have been estimated, fit statistics can be computed.
- computeItemScore(String) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
-
First checks for missing data.
- computeItemScore(double) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
-
- computeItemScore(int) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
-
- computeItemScore(Object) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
Missing responses, omitted responses, and not reached responses are scored according to the value in
the SepcialDataCodes object.
- computeItemScore(Object) - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
-
- computeItemStandardErrors() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
-
Item difficulty standard error calculation.
- computeItemStandardErrors() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
-
- computeMaximumPossibleTestScore() - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
-
- computeMissingScore(String) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
-
Computes the score associated with a missing data code.
- computeMissingScore(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
-
- computeMissingScore(double) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
-
- computeMissingScore(int) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
-
- computePersonStandardErrors() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
-
Person ability parameter standard error calculation.
- computePersonStandardErrors() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScoreTable
-
Person ability parameter standard error calculation.
- computeRaschItemFit() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
-
- computeScoreVector(Object) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
-
Creates an array of category keys and their corresponding score for the response.
- computeStartingValues() - Method in class com.itemanalysis.psychometrics.irt.estimation.StartingValues
-
The public method for computing start values.
- computeSX2ItemFit(int) - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
-
- computeValues(RealMatrix) - Method in class com.itemanalysis.psychometrics.factoranalysis.GeominCriteria
-
- computeValues(RealMatrix) - Method in class com.itemanalysis.psychometrics.factoranalysis.ObliminCriteria
-
- computeValues(RealMatrix) - Method in class com.itemanalysis.psychometrics.factoranalysis.QuartiminCriteria
-
- computeValues(RealMatrix) - Method in interface com.itemanalysis.psychometrics.factoranalysis.RotationCriteria
-
- computeValues(RealMatrix) - Method in class com.itemanalysis.psychometrics.factoranalysis.VarimaxCriteria
-
Computes the function value for varimax rotation.
- condenseTable() - Method in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
-
- condenseTable() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitSX2
-
- ConditionalNumericItemResponseSummary - Class in com.itemanalysis.psychometrics.measurement
-
A class for summarizing item responses conditional on a test score.
- ConditionalNumericItemResponseSummary(VariableName) - Constructor for class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
-
- ConditionalSEM - Class in com.itemanalysis.psychometrics.reliability
-
- ConditionalSEM(Integer[], double, ScoreReliability, KR21, boolean) - Constructor for class com.itemanalysis.psychometrics.reliability.ConditionalSEM
-
- ConditionalTextItemResponseSummary - Class in com.itemanalysis.psychometrics.measurement
-
Item response summary conditional on a test score.
- ConditionalTextItemResponseSummary(VariableName) - Constructor for class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
-
- confidenceInterval() - Method in class com.itemanalysis.psychometrics.reliability.AbstractScoreReliability
-
This confidence interval applies to Coefficient alpha because it has a known sampling distribution.
- confidenceInterval() - Method in class com.itemanalysis.psychometrics.reliability.ReliabilityInterval
-
- confidenceInterval() - Method in interface com.itemanalysis.psychometrics.reliability.ScoreReliability
-
Confidence interval for the reliability estimate computed using the F-distribution.
- confidenceIntervalToString(double[]) - Method in class com.itemanalysis.psychometrics.reliability.AbstractScoreReliability
-
- confidenceIntervalToString(double[]) - Method in interface com.itemanalysis.psychometrics.reliability.ScoreReliability
-
Creates a String representation of the confidence interval.
- contains(int[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- containsInSubarray(int[], int, int, int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- ContinuousDistributionApproximation - Class in com.itemanalysis.psychometrics.distribution
-
A class that provides a discrete approximation of a univariate continuous probability distribution.
- ContinuousDistributionApproximation(int, double, double) - Constructor for class com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation
-
Constructor for using starting values from a uniform distribution.
- ContinuousDistributionApproximation(int, double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation
-
Constructor for using starting values from a normal distribution.
- ContinuousDistributionApproximation(double[], double[]) - Constructor for class com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation
-
Construct the object using the supplied arrays of points and weights.
- converged() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
-
- copyOf(double[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
Simulate Arrays.copyOf method provided by Java 6
When/if the JavaNLP-core code base moves past Java 5, this method can be removed
- correctedValue() - Method in class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
-
Correct correlation for spuriousness.
- correlation() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
-
- correlation() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
-
- correlation() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
-
- correlation() - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
-
- correlationPvalue() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
-
- correlationStandardError() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
-
- CosineKernel - Class in com.itemanalysis.psychometrics.kernel
-
- CosineKernel() - Constructor for class com.itemanalysis.psychometrics.kernel.CosineKernel
-
- count(Object, Double) - Method in class com.itemanalysis.psychometrics.cmh.CmhTableRow
-
- countCloseToZero(double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- countInfinite(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- countNaN(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- countNegative(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- countNonZero(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- countPositive(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- covariance(double[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- Covariance - Class in com.itemanalysis.psychometrics.polycor
-
- Covariance(boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- Covariance() - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- Covariance(double, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- Covariance(double) - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- Covariance(Covariance, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- Covariance(Covariance) - Constructor for class com.itemanalysis.psychometrics.polycor.Covariance
-
- CovarianceMatrix - Class in com.itemanalysis.psychometrics.polycor
-
Computes NxN covariance and correlation matrix.
- CovarianceMatrix(double[][], boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
-
Input is a two-array of doubles.
- CovarianceMatrix(double[][]) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
-
- CovarianceMatrix(ArrayList<VariableAttributes>, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(ArrayList<VariableAttributes>) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(LinkedHashMap<VariableName, VariableAttributes>, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(LinkedHashMap<VariableName, VariableAttributes>) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(int, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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This constructor is primarily used in the TestSummary.java class.
- CovarianceMatrix(int) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(Covariance[][], ArrayList<VariableAttributes>, boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- CovarianceMatrix(Covariance[][], ArrayList<VariableAttributes>) - Constructor for class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- covarianceSum() - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- createLookupTable(PercentileRank, LinearTransformation) - Method in class com.itemanalysis.psychometrics.scaling.NormalizedScore
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Creates a TreeMap lookup table of normalized scores.
- createLookupTable() - Method in class com.itemanalysis.psychometrics.scaling.PercentileRank
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Creates a TreeMap lookup table of percentile ranks.
- CSEM - Class in com.itemanalysis.psychometrics.reliability
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- CSEM(double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.reliability.CSEM
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- CSEMList - Class in com.itemanalysis.psychometrics.reliability
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- CSEMList(double, double, double) - Constructor for class com.itemanalysis.psychometrics.reliability.CSEMList
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- cumulativeColumnSums() - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- cumulativeProbability(double[], double[], double[][]) - Method in class com.itemanalysis.psychometrics.distribution.BivariateNormalDistributionImpl
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A function for computing bivariate normal probabilities.
- cumulativeProbability(double[], double[], int[], double) - Method in class com.itemanalysis.psychometrics.distribution.BivariateNormalDistributionImpl
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A function for computing bivariate normal probabilities.
- cumulativeProbability(double[], double[], double) - Method in class com.itemanalysis.psychometrics.distribution.BivariateNormalDistributionImpl
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A function for computing bivariate normal probabilities.
- cumulativeProbability(double, double, double) - Method in class com.itemanalysis.psychometrics.distribution.BivariateNormalDistributionImpl
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A function for computing bivariate normal probabilities.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
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Not implemented.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
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Not implemented.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
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Not implemented.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
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Not implemented.
- cumulativeProbability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
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- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
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Compute cumulative probability of scoring at or above category.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
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Not implemented.
- cumulativeProbability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
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Not implemented.
- cumulativeProbability(double, int) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
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Mainly here for the graded response model
- cumulativeRowSums() - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- Cut - Class in com.itemanalysis.psychometrics.histogram
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Cuts a continuous variable into numberOfBins intervals that range from
min to max.
- Cut(double, double, int, boolean) - Constructor for class com.itemanalysis.psychometrics.histogram.Cut
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- Cut(double, double, int) - Constructor for class com.itemanalysis.psychometrics.histogram.Cut
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- cvSum(double) - Method in class com.itemanalysis.psychometrics.kernel.LeastSquaresCrossValidation
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