P-Index

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P

pairwiseAdd(int[], int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseAdd(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseAdd(float[], float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseAddInPlace(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseAddInPlace(double[], int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseAddInPlace(double[], short[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseDivideInPlace(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Divide the first array by the second elementwise, and store results in place.
pairwiseMultiply(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Assumes that both arrays have same length.
pairwiseMultiply(float[], float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Assumes that both arrays have same length.
pairwiseMultiply(double[], double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Puts the result in the result array.
pairwiseMultiply(float[], float[], float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Puts the result in the result array.
pairwiseScaleAdd(double[], double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseScaleAddInPlace(double[], double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseSubtract(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseSubtract(float[], float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
pairwiseSubtractInPlace(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
parseMethod(String) - Static method in enum com.itemanalysis.psychometrics.optimization.StochasticCalculateMethods
parseSpecialCodeString(String) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes: Parses the code string that has the format (NA,OM,NR)(-1,-1,-1).
partialDerivative(int) - Method in class com.itemanalysis.psychometrics.analysis.AbstractDiffFunction
partialDerivative(int) - Method in class com.itemanalysis.psychometrics.analysis.AbstractMultivariateFunction
pcfEstimate(int, double, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee: Computes ability estimate using proportional curve fitting.
pcfStandardErrorAt(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
pearsonCorrelation(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Direct computation of Pearson product-moment correlation coefficient.
PearsonCorrelation - Class in com.itemanalysis.psychometrics.polycor: This class is mainly a short-cut for the Pearson correlation.
PearsonCorrelation(boolean) - Constructor for class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
PearsonCorrelation() - Constructor for class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
PercentileRank - Class in com.itemanalysis.psychometrics.scaling
PercentileRank(Integer, Integer) - Constructor for class com.itemanalysis.psychometrics.scaling.PercentileRank
PercentileRank() - Constructor for class com.itemanalysis.psychometrics.scaling.PercentileRank
PERMANENT_MISSING_DATA_CODE - Static variable in class com.itemanalysis.psychometrics.data.SpecialDataCodes
PersonScoringType - Enum in com.itemanalysis.psychometrics.irt.estimation
pF() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel: Computes the standardized mean difference (SMD).
points - Variable in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
poisson(int, double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
PolychoricCorrelation - Interface in com.itemanalysis.psychometrics.polycor
PolychoricMaximumLikelihood - Class in com.itemanalysis.psychometrics.polycor
PolychoricMaximumLikelihood(double[][]) - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
PolychoricMaximumLikelihood(TwoWayTable) - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
PolychoricMaximumLikelihood() - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood: Constructor for incrementally updating data
PolychoricMaximumLikelihood.MaximumLikelihoodFunction - Class in com.itemanalysis.psychometrics.polycor
PolychoricTwoStep - Class in com.itemanalysis.psychometrics.polycor
PolychoricTwoStep(double[][]) - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricTwoStep: Constructor for use when data have been summarized in an row x column frequency table.
PolychoricTwoStep(TwoWayTable) - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricTwoStep: Constructor for use when data have been summarized in a TwoWayTable.
PolychoricTwoStep() - Constructor for class com.itemanalysis.psychometrics.polycor.PolychoricTwoStep: Constructor for incrementally updating the data.
PolychoricTwoStep.TwoStepLikelihoodFunction - Class in com.itemanalysis.psychometrics.polycor: Likelihood function for the two-step approximation.
PolyserialCorrelation - Interface in com.itemanalysis.psychometrics.polycor
PolyserialLogLikelihoodTwoStep - Class in com.itemanalysis.psychometrics.polycor
PolyserialLogLikelihoodTwoStep(double[], int[]) - Constructor for class com.itemanalysis.psychometrics.polycor.PolyserialLogLikelihoodTwoStep
PolyserialMaximumLikelihood - Class in com.itemanalysis.psychometrics.polycor
PolyserialMaximumLikelihood(double[], int[]) - Constructor for class com.itemanalysis.psychometrics.polycor.PolyserialMaximumLikelihood
PolyserialMaximumLikelihood() - Constructor for class com.itemanalysis.psychometrics.polycor.PolyserialMaximumLikelihood: Constructor for incrmentally updating object with data.
PolyserialPlugin - Class in com.itemanalysis.psychometrics.polycor: This class computes the polyserial correlation between a continuous X variable and an ordered categorical Y variable.
PolyserialPlugin() - Constructor for class com.itemanalysis.psychometrics.polycor.PolyserialPlugin
PolyserialTwoStep - Class in com.itemanalysis.psychometrics.polycor
PolyserialTwoStep(Mean, StandardDeviation, double[], double[], PearsonCorrelation) - Constructor for class com.itemanalysis.psychometrics.polycor.PolyserialTwoStep
populationStandardDeviation() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: Population standard deviation (i.e.
populationVariance() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: Computes a weighted population variance (i.e.
positionInDb() - Method in class com.itemanalysis.psychometrics.data.VariableAttributes: Mostly used for ordering variables according to their order in the database or result set
posteriorProbability(int, int) - Method in interface com.itemanalysis.psychometrics.mixture.MixtureModel
posteriorProbability(int, int) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
pow(double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: raises each entry in array a by power c
pow(float[], float) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: raises each entry in array a by power c
pow(double, double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Returns an approximation to Math.pow(a,b) that is ~27x faster with a margin of error possibly around ~10%.
powInPlace(double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Scales the values in this array by c.
powInPlace(float[], float) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Sets the values in this array by to their value taken to cth power.
precision - Variable in class com.itemanalysis.psychometrics.scaling.ScoreBounds
PrincipalComponentsMethod - Class in com.itemanalysis.psychometrics.factoranalysis: Principal components analysis.
PrincipalComponentsMethod(RealMatrix, int, RotationMethod) - Constructor for class com.itemanalysis.psychometrics.factoranalysis.PrincipalComponentsMethod
print(boolean) - Method in class com.itemanalysis.psychometrics.irt.equating.RobustZEquatingTest
print() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
print() - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
print() - Method in interface com.itemanalysis.psychometrics.polycor.PolychoricCorrelation
print() - Method in class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
print() - Method in class com.itemanalysis.psychometrics.polycor.PolychoricTwoStep
print() - Method in interface com.itemanalysis.psychometrics.polycor.PolyserialCorrelation
print() - Method in class com.itemanalysis.psychometrics.polycor.PolyserialMaximumLikelihood
print() - Method in class com.itemanalysis.psychometrics.reliability.ConditionalSEM
print() - Method in class com.itemanalysis.psychometrics.reliability.ReliabilityInterval
printAttributes() - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
printBasicItemStats() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
printBasicItemStats(String) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: This method is for displaying item parameter estimates, standard errors, and other information.
printCategoryStats() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: Polytomous items have a set of threshold statistics that must be reported.
printContingencyTable(String, boolean) - Method in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
printCorrelationMatrix(boolean) - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
printCorrelationMatrix(boolean) - Method in class com.itemanalysis.psychometrics.polycor.MixedCorrelationMatrix
printCorrelationTypes() - Method in class com.itemanalysis.psychometrics.polycor.MixedCorrelationMatrix
printCovariance() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
printCovarianceMatrix() - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
printDelimitedFit() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
printDelimitedFitStatistics() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
printFit() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
printFitStatistics() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
printFrequencyTables() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: This method is for displaying frequency tables for each item.
printHeader() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
printHeader() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem: Header for the item analysis output.
printHistory() - Method in interface com.itemanalysis.psychometrics.mixture.MixtureModel
printHistory() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.CoefficientAlpha
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.FeldtBrennan
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.FeldtGilmer
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.GuttmanLambda
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.KR21
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.reliability.RajuBeta
printItemDeletedSummary(ArrayList<VariableAttributes>) - Method in interface com.itemanalysis.psychometrics.reliability.ScoreReliability: A String representation of all item deleted reliability estimates.
printItemFitStatistics() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
printItemParameters() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
printItemParameters() - Method in class com.itemanalysis.psychometrics.irt.estimation.StartingValues
printItemStats(String) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: Creates a string of item statistics.
printIterationHistory() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: Joint maximum likelihood estimation is iterative.
printLatentDistribution() - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
printMatrix(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
printMean() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
printMirtFormatTable(boolean) - Method in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic: Prints output in similar way to mirt package in R.
printMixingProportion() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
printNameChangeInformation() - Method in class com.itemanalysis.psychometrics.data.VariableName
printOptionScoreKey() - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
printOptionScoreKey() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring: this method creates a String that represents the item scoring.
printOptionScoreKey() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
printOutput() - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
printOutput(String) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
printOutput(String, int) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
printOutput(int) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis: Formatted output of the results.
printPersonStats() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: This method is for displaying person parameter estimates, standard errors, and other information.
printPolychoricThresholds() - Method in class com.itemanalysis.psychometrics.polycor.MixedCorrelationMatrix
printRatingScaleTables() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: This method is for displaying frequency tables for polytomous items.
printRecord() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
printResponseVector() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
printResults() - Method in class com.itemanalysis.psychometrics.irt.equating.IrtTrueScoreEquating: Display results in text format with this method.
printResults() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
printScaleQuality() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityOutput: Gets a string with the formatted scale quality output.
printScoreTable(int, double, double, DefaultLinearTransformation, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: The sum score is a sufficient statistic for the latent trait in the Rasch family of models.
printScoreTable() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScoreTable: The score table is formatted for output here.
printStartValues() - Method in class com.itemanalysis.psychometrics.factoranalysis.MINRESmethod
printTable(int) - Method in class com.itemanalysis.psychometrics.scaling.NormalizedScore
printTables() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel: From 1999 South Carolina PACT Technical Documentation
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Comute the probability of a correct response.
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Computes probability of a correct response using value provided to the method, not the parameters stored in the object.
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Computes the probability of a correct response given parameters stored in the object.
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM: Computes the probability of responding in category k using item parameters passed to the method using the iparam argument.
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM: Computes probability of a response using parameters stored in the object.
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2: Computes probability of a response using parameters stored in the object.
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM: Computes probability of a response using parameters stored in the object.
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM: Computes probability of a response using parameters stored in the object.
probability(double, double[], int, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2: Computes the probability of responding in category k using item parameters passed to the method using the iparam argument.
probability(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2: Computes probability of a response using parameters stored in the object.
probability(double, int) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Computes the probability of response.
probability(double, double[], int, double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Computes the probability of a response using item parameter values passed in iparam.
probabilitySumAt(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup: Sums the probability of responding in category at position k over all items in this rating scale group.
probChiSquare - Variable in class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
proportionOfExplainedVariance - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
proportionOfVariance - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
proposalStep - Variable in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
pythonMod(int, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Returns a mod where the sign of the answer is the same as the sign of the second argument.

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