- eapEstimate(double, double, double, double, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
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Expected a Posteriori (EAP) estimate of examinee ability using a normal distribution.
- eapEstimate(DistributionApproximation) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
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EAP estimate using a distribution provided by the user such as quadrature points
and weights from item calibration.
- eapStandardErrorAt(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
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Computes standard error for EAP method.
- empiricalHistogramLatentDensityEstimation() - Method in class com.itemanalysis.psychometrics.irt.estimation.MstepParallel
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Nonparametric estimation (empirical histogram method) of the latent density.
- EMStatusEventObject - Class in com.itemanalysis.psychometrics.irt.estimation
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- EMStatusEventObject(Object) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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- EMStatusEventObject(Object, String) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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- EMStatusEventObject(Object, String, int, double, double, String) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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Used for EM and start value cycle information
- EMStatusEventObject(Object, String, int, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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- EMStatusEventObject(Object, int, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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Use for EM cycle information only
- EMStatusEventObject(Object, int, double, double, String) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EMStatusEventObject
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- EMStatusListener - Interface in com.itemanalysis.psychometrics.irt.estimation
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- entropy() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
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- entropy(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- EpanechnikovKernel - Class in com.itemanalysis.psychometrics.kernel
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- EpanechnikovKernel() - Constructor for class com.itemanalysis.psychometrics.kernel.EpanechnikovKernel
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- EPSILON - Static variable in class com.itemanalysis.psychometrics.measurement.MachineAccuracy
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machine accuracy constant
- equals(Object) - Method in class com.itemanalysis.psychometrics.data.Category
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- equals(Object) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
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- equals(Object) - Method in class com.itemanalysis.psychometrics.data.VariableLabel
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- equals(Object) - Method in class com.itemanalysis.psychometrics.data.VariableName
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- equals(Object) - Method in class com.itemanalysis.psychometrics.data.VariableType
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- equals(Object) - Method in class com.itemanalysis.psychometrics.histogram.Bin
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Evaluates the equality of of two bins.
- equals(Object) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
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- equals(Object) - Method in class com.itemanalysis.psychometrics.polycor.Covariance
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- equals(Object) - Method in class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
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- equals(Object) - Method in class com.itemanalysis.psychometrics.reliability.AbstractScoreReliability
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- equals(Object) - Method in class com.itemanalysis.psychometrics.reliability.ConditionalSEM
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- equals(Object) - Method in class com.itemanalysis.psychometrics.reliability.CSEM
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- equals(Object) - Method in class com.itemanalysis.psychometrics.scaling.RawScore
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- equateScores() - Method in class com.itemanalysis.psychometrics.irt.equating.IrtTrueScoreEquating
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Primary method for conducting the IRT true score equating.
- EquatingCriterionType - Enum in com.itemanalysis.psychometrics.irt.equating
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- EstepEstimates - Class in com.itemanalysis.psychometrics.irt.estimation
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- EstepEstimates(int, int[], int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EstepEstimates
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- EstepItemEstimates - Class in com.itemanalysis.psychometrics.irt.estimation
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Stores the count of the expected number of responses to category k for item j.
- EstepItemEstimates(int, int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EstepItemEstimates
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- EstepParallel - Class in com.itemanalysis.psychometrics.irt.estimation
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Estep of the EM algorithm for estimating item parameters in MMLE.
- EstepParallel(ItemResponseVector[], ItemResponseModel[], DistributionApproximation, int, int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.EstepParallel
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Default constructor may be called recursively for parallel computations.
- estimateCov(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
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- estimateMean(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
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- estimateParameters(EstimationMethod, RotationMethod) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
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The main method for estimating parameters.
- estimateParameters(EstimationMethod) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
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- estimateParameters() - Method in interface com.itemanalysis.psychometrics.factoranalysis.FactorMethod
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A method for estimating parameters.
- estimateParameters() - Method in class com.itemanalysis.psychometrics.factoranalysis.GeneralizedLeastSquaresMethod
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- estimateParameters() - Method in class com.itemanalysis.psychometrics.factoranalysis.MaximumLikelihoodMethod
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- estimateParameters() - Method in class com.itemanalysis.psychometrics.factoranalysis.MINRESmethod
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- estimateParameters() - Method in class com.itemanalysis.psychometrics.factoranalysis.PrincipalComponentsMethod
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- estimateParameters() - Method in class com.itemanalysis.psychometrics.factoranalysis.WeightedLeastSquaresMethod
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- estimateParameters(int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
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A shortcut method that only requires input for the maximum number of global iterations and the global
convergence criterion.
- estimateParameters(int, double, boolean) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
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A shortcut method that only requires input for the maximum number of global iterations and the global
convergence criterion.
- estimateParameters(int, double, int, double, boolean) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
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This method is where the estimation is managed.
- estimateParameters(double, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
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Estimate parameters using the specified convergence criterion and maximum number of iterations.
- estimateParameters(double, int, DensityEstimationType) - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
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The EM algorithm for estimating item parameters is conducted with this method.
- EstimationMethod - Enum in com.itemanalysis.psychometrics.factoranalysis
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- EstimationMethod - Enum in com.itemanalysis.psychometrics.irt.estimation
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- etsBinayClassification(double, double, double) - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
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- etsDelta(double) - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
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- evaluate() - Method in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
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- evaluate() - Method in interface com.itemanalysis.psychometrics.distribution.DistributionApproximation
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Gets and array of density values.
- evaluate(double[]) - Method in class com.itemanalysis.psychometrics.histogram.AbstractBinCalculation
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- evaluate() - Method in class com.itemanalysis.psychometrics.histogram.Histogram
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Gets an array of value values.
- evaluate(double[]) - Method in class com.itemanalysis.psychometrics.histogram.Histogram
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- evaluate() - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity
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Call this method when using the incremental update to the density estimator.
- evaluate(double[]) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity
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Call tihs method when not using the incremental update.
- evaluate(double[], int) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity
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Leave one out kernel evaluate estimate.
- evaluate(double[], double[]) - Method in class com.itemanalysis.psychometrics.kernel.LocalLinearRegression
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- evaluate(double[], byte[]) - Method in class com.itemanalysis.psychometrics.kernel.LocalLinearRegression
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- evaluate(double[]) - Method in interface com.itemanalysis.psychometrics.optimization.Evaluator
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- evaluate(PercentileRank, DefaultLinearTransformation) - Method in class com.itemanalysis.psychometrics.scaling.NormalizedScore
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For r number of score levels between min and max (as defined in PercentileRank),
inclusive, this method returns a r x 2 array with integer based scores in first
column and normalized scores in the second column.
- evaluate() - Method in class com.itemanalysis.psychometrics.scaling.PercentileRank
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For r number of score levels between min and max, inclusive, this method
returns a r x 2 array with integer based scores in first column
and percentile ranks in the second column.
- evaluate(int[]) - Method in class com.itemanalysis.psychometrics.scaling.PercentileRank
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- evaluate(double[]) - Method in class com.itemanalysis.psychometrics.scaling.PercentileRank
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- evaluate(double[]) - Method in class com.itemanalysis.psychometrics.statistics.Bootstrap
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- Evaluator - Interface in com.itemanalysis.psychometrics.optimization
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- exactBinomial(int, int, double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
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Find a one tailed exact binomial test probability.
- ExampleMultivariateFunction - Class in com.itemanalysis.psychometrics.analysis
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An instantiation of AbstractMultivariateFunction for testing purposes only.
- ExampleMultivariateFunction(int) - Constructor for class com.itemanalysis.psychometrics.analysis.ExampleMultivariateFunction
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- exp(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- expectedValue() - Method in class com.itemanalysis.psychometrics.cmh.CmhTable
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- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
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Computes the expected value
- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
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Computes the expected value, which is the same as the probability of a correct response.
- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
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Computes the expected value using parameters stored in the object.
- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
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computes the expected value using parameters stored in the object
- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
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- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
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computes the expected value using parameters stored in the object
- expectedValue(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
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Computes the expected value using parameters stored in the object.
- expectedValue(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
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- expectedValues - Variable in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
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- expInPlace(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- ExploratoryFactorAnalysis - Class in com.itemanalysis.psychometrics.factoranalysis
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This class is the main entry point for conducting exploratory factor analysis.
- ExploratoryFactorAnalysis(RealMatrix, int) - Constructor for class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
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The constructor requires a correlation matrix and the number of factors.
- extractColumnThresholds(double[], boolean) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- extractRho(double[], boolean) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- extractRowThresholds(double[], boolean) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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