S-Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

S

sabic() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
sacaic() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
safeMax(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the largest value in a vector of doubles.
safeMean(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the mean of a vector of doubles.
safeMin(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the largest value in a vector of doubles.
safeStdev(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the standard deviation of a vector of doubles.
same(double, double) - Static method in class com.itemanalysis.psychometrics.measurement.MachineAccuracy
sameItemGroup(ItemResponseSummary) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Compares this item summary to another one to determine of they belong to the same item group.
sampleFromDistribution(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Samples from the distribution over values 0 through d.length given by d.
sampleFromDistribution(double[], Random) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Samples from the distribution over values 0 through d.length given by d.
sampleFromDistribution(float[], Random) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Samples from the distribution over values 0 through d.length given by d.
sampleSize() - Method in class com.itemanalysis.psychometrics.histogram.AbstractBinCalculation: Gets the sample size.
sampleSize() - Method in interface com.itemanalysis.psychometrics.mixture.MixtureModel
sampleSize() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
sampleSize() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
sampleSize() - Method in class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
sampleStandardDeviation() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: Sample standard deviation (i.e.
sampleVariance() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: Computes a weighted sample variance (i.e.
sampleWithoutReplacement(int[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Fills the array with sample from 0 to numArgClasses-1 without replacement.
sampleWithoutReplacement(int[], int, Random) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Fills the array with sample from 0 to numArgClasses-1 without replacement.
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Linear transformation of item parameters.
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Linear transformation of item parameters.
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM: Computes a linear transformation of item parameters.
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
scale(double, double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2: Computes a linear transformation of item parameters.
scale(double, double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Performs a linear transformation of item parameters and standard errors.
scaleOpt - Variable in class com.itemanalysis.psychometrics.optimization.QNMinimizer.QNInfo
sclmul_f77(int, double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin: The sclmul_f77 method multiplies a vector by a scalar.
sclmul_f77(int, double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77: The sclmul_f77 method multiplies a vector by a scalar.
scoreArray() - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
scoreArray() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring: this method creates a double array of all existing options scores.
scoreArray() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
ScoreBounds - Class in com.itemanalysis.psychometrics.scaling
ScoreBounds() - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreBounds: Use this constructor for the default bounds of negative and positive infinity
ScoreBounds(int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreBounds: Use this constructor for the default bounds of negative and positive infinity It also allows precision to be set.
ScoreBounds(Double, Double) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreBounds: Use this constructor for providing starting values for an incremental update.
ScoreBounds(Double, Double, int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreBounds: Use this constructor for providing starting values for an incremental update.
ScoreBounds(ArrayList<VariableAttributes>, int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreBounds
ScoreReliability - Interface in com.itemanalysis.psychometrics.reliability
ScoreReliabilityType - Enum in com.itemanalysis.psychometrics.reliability: Copyright 2012 J.
ScoreTable - Class in com.itemanalysis.psychometrics.scaling
ScoreTable(ScoreBounds) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreTable
ScoreTable(ScoreBounds, String) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreTable
ScoreTable(ScoreBounds, int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreTable
ScoreTable(ScoreBounds, String, int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreTable
ScoreTable(ScoreBounds, Double, String, int) - Constructor for class com.itemanalysis.psychometrics.scaling.ScoreTable
scoreValue() - Method in class com.itemanalysis.psychometrics.data.Category
scoreWeight - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
scoreWeight - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
ScottBinCalculation - Class in com.itemanalysis.psychometrics.histogram: Scott's method form computing the number of bins in a histogram.
ScottBinCalculation(double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.histogram.ScottBinCalculation
ScottsBandwidth - Class in com.itemanalysis.psychometrics.kernel: See Silverman (1986, p.
ScottsBandwidth(double[]) - Constructor for class com.itemanalysis.psychometrics.kernel.ScottsBandwidth
ScottsBandwidth(double[], double) - Constructor for class com.itemanalysis.psychometrics.kernel.ScottsBandwidth
sd - Variable in class com.itemanalysis.psychometrics.histogram.AbstractBinCalculation: Standard deviation of values.
sdX() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
sdY() - Method in class com.itemanalysis.psychometrics.polycor.Covariance
secfac_f77(int, double[], double[], double[][], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin: The secfac_f77 method updates the Hessian by the BFGS factored technique.
secfac_f77(int, double[], double[], double[][], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77: The secfac_f77 method updates the Hessian by the BFGS factored technique.
secunf_f77(int, double[], double[], double[][], double[], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin: The secunf_f77 method updates the Hessian by the BFGS unfactored approach.
secunf_f77(int, double[], double[], double[][], double[], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77: The secunf_f77 method updates the Hessian by the BFGS unfactored approach.
separationIndex() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityStatistics: The separation index of scale quality.
setAllCellPadding(int) - Method in class com.itemanalysis.psychometrics.texttable.TextTable
setCellPadding(int) - Method in class com.itemanalysis.psychometrics.texttable.TextTableRow
setColVariable(VariableAttributes) - Method in class com.itemanalysis.psychometrics.statistics.TwoWayTable
setConstraints(Double, Double) - Method in class com.itemanalysis.psychometrics.scaling.ScoreBounds: Constraint the min and max possible values.
setCovariance(RealMatrix) - Method in interface com.itemanalysis.psychometrics.mixture.ComponentDistribution
setCovariance(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
setData(double[]) - Method in class com.itemanalysis.psychometrics.histogram.Histogram
setDataType(DataType) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setDataType(DataType) - Method in class com.itemanalysis.psychometrics.data.VariableType
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation
setDensityAt(int, double) - Method in interface com.itemanalysis.psychometrics.distribution.DistributionApproximation
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.NormalDistributionApproximation
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.UniformDistributionApproximation
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.UserSuppliedDistributionApproximation: Deprecated.
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.histogram.Histogram
setDensityAt(int, double) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Set difficulty parameter to an existing value.
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Set difficulty parameter to an existing value.
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDifficulty(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set difficulty parameter to an existing value.
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDifficultyPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDifficultyPrior(ItemParamPrior) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Item difficulty standard error may be computed external to the class.
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Item difficulty standard error may be computed external to the class.
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDifficultyStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDifficultyStdError(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Item difficulty standard error may be computed external to the class.
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Set discrimination parameter to an existing value.
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Set discrimination parameter to an existing value.
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDiscrimination(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set discrimination parameter to an existing value.
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDiscriminationPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDiscriminationPrior(ItemParamPrior) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: The standard error may be computed external to the class.
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: The standard error may be computed external to the class.
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setDiscriminationStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setDiscriminationStdError(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: The standard error may be computed external to the class.
setDoubleFormat(int, int, TextTableColumnFormat.OutputAlignment) - Method in class com.itemanalysis.psychometrics.texttable.TextTableColumnFormat
setEmOptions(int, double, int) - Method in interface com.itemanalysis.psychometrics.mixture.MixtureModel
setEmOptions(int, double, int) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
setEPS(double) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.Record
setEvaluators(int, Evaluator[]) - Method in interface com.itemanalysis.psychometrics.optimization.HasEvaluators
setEvaluators(int, Evaluator[]) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setEvaluators(int, int, Evaluator[]) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setFixed(boolean) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel: If parameters can be estimated, the isFixed should be false.
setFixed(boolean) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient: If parameters can be estimated, the isFixed should be false.
setFixed(boolean) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: A fixed item will use its initial values as the item parameters and no further estimation or update will be applied to the item parameters.
setFrequency(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
setGroupId(String) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
setGroupId(String) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
setGroupId(String) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: An item may be assigned to a group of items.
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Set lower asymptote parameter to an existing value.
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Set lower asymptote parameter to an existing value.
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setGuessing(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set lower asymptote parameter to an existing value.
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setGuessingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setGuessingPrior(ItemParamPrior) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: The guessing parameter standard error may be computed external to the class.
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: The guessing parameter standard error may be computed external to the class.
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setGuessingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setGuessingStdError(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: The guessing parameter standard error may be computed external to the class.
setHaebaraCritionType(EquatingCriterionType) - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
setHighDiscrimination(double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
setHighPvalue(double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
setHistory(List<double[]>, List<double[]>) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.QNInfo
setHistory(List<double[]>, List<double[]>) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setId(String) - Method in class com.itemanalysis.psychometrics.statistics.RobustZ
setIndex(int) - Method in class com.itemanalysis.psychometrics.data.VariableName
setIntercept(double) - Method in class com.itemanalysis.psychometrics.irt.equating.HaebaraMethod
setIntercept(double) - Method in class com.itemanalysis.psychometrics.irt.equating.StockingLordMethod
setIntercept(double) - Method in class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
setIntFormat(int, TextTableColumnFormat.OutputAlignment) - Method in class com.itemanalysis.psychometrics.texttable.TextTableColumnFormat
setItemFitStatistic(ItemFitStatistic) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
setItemFitStatistic(ItemFitStatistic) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
setItemFitStatistic(ItemFitStatistic) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setItemGroup(String) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setItemScoring(ItemScoring) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setItemScoring(ItemScoring) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
setItemScoring(ItemScoring) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
setItemScoring(ItemScoring) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setItemType(ItemType) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setItemType(ItemType) - Method in class com.itemanalysis.psychometrics.data.VariableType
setItemType(String) - Method in class com.itemanalysis.psychometrics.data.VariableType
setLabel(String) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setLength(int) - Method in class com.itemanalysis.psychometrics.data.VariableLabel
setLowDiscrimination(double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
setLowPvalue(double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
setM(int) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setMatrix(double[]) - Method in class com.itemanalysis.psychometrics.measurement.DiagonalMatrix: Changes the diagonal of the matrix to the values in x.
setMatrix() - Method in class com.itemanalysis.psychometrics.statistics.IdentityMatrix
setMatrix() - Method in class com.itemanalysis.psychometrics.statistics.IdentityVector
setMean(RealMatrix) - Method in interface com.itemanalysis.psychometrics.mixture.ComponentDistribution
setMean(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
setMissingDataCode(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setMissingDataScore(double) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setMixingProportion(double) - Method in interface com.itemanalysis.psychometrics.mixture.ComponentDistribution
setMixingProportion(double) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
setModel(ItemResponseModel, DistributionApproximation, EstepItemEstimates, double[]) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood
setModel(ItemResponseModel, DistributionApproximation, EstepItemEstimates, double[]) - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihoodFunction
setModel() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemPolytomous
setModelConstraints(boolean, boolean, boolean, boolean) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
setName(VariableName) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setName(VariableName) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
setName(VariableName) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
setName(VariableName) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setName(VariableName) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Sets the name of the item.
setNameAt(int, VariableName) - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
setNameAt(int, String) - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
setNames(ArrayList<VariableName>, ArrayList<VariableName>) - Method in class com.itemanalysis.psychometrics.irt.equating.RobustZEquatingTest
setNormalPointsAndWeights(double, double) - Method in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
setNotReachedCode(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setNotReachedScore(double) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setOldOptions() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setOmittedCode(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setOmittedScore(double) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation
setPointAt(int, double) - Method in interface com.itemanalysis.psychometrics.distribution.DistributionApproximation
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.NormalDistributionApproximation
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.UniformDistributionApproximation
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.distribution.UserSuppliedDistributionApproximation: Deprecated.
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.histogram.Histogram
setPointAt(int, double) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity
setPositionInArray(int) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Stores the item's position in the array of item response models.
setPosteriorProbability(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
setPrecision(int) - Method in class com.itemanalysis.psychometrics.irt.equating.HaebaraMethod
setPrecision(int) - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
setPrecision(int) - Method in class com.itemanalysis.psychometrics.irt.equating.MeanMeanMethod
setPrecision(int) - Method in class com.itemanalysis.psychometrics.irt.equating.MeanSigmaMethod
setPrecision(int) - Method in class com.itemanalysis.psychometrics.irt.equating.StockingLordMethod
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: A proposal difficulty value is obtained during each iteration of the estimation routine.
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: A proposal difficulty value is obtained during each iteration of the estimation routine.
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalDifficulty(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalDifficulty(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: A proposal difficulty value is obtained during each iteration of the estimation routine.
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Set the proposed discrimination estimate.
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Set the proposed discrimination estimate.
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalDiscrimination(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalDiscrimination(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set the proposed discrimination estimate.
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: A proposal guessing parameter value is obtained during each iteration of the estimation routine.
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: A proposal guessing parameter value is obtained during each iteration of the estimation routine.
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalGuessing(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalGuessing(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: A proposal guessing parameter value is obtained during each iteration of the estimation routine.
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: A proposal slipping parameter value is obtained during each iteration of the estimation routine.
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalSlipping(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: A proposal slipping parameter value is obtained during each iteration of the estimation routine.
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalStepParameters() - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalStepParameters(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setProposalThresholds(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Sets the proposed threshold parameters estimates to particular values.
setProposalThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup: Sets the array of proposal values.
setResponseVector(ItemResponseVector) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee: If the response vector was not set in teh constructor, this method must be called prior to estimating ability.
setResponseVector(byte[]) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
setResponseVector(byte[]) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: Use this method to add an entire item response vector for a single examinee.
setRobustOptions() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setRowVariable(VariableAttributes) - Method in class com.itemanalysis.psychometrics.statistics.TwoWayTable
setScale(double) - Method in class com.itemanalysis.psychometrics.irt.equating.HaebaraMethod
setScale(double) - Method in class com.itemanalysis.psychometrics.irt.equating.StockingLordMethod
setScale(double) - Method in class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
setScaleAndIntercept(double, double, double, double) - Method in class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
setScoreAt(String, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
setScoreAt(int, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
setScoreAt(double, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
setScoreAt(String, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Sets the value of a response to that given by score.
setScoreAt(int, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Sets the value of a response to that given by score.
setScoreAt(double, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Sets the value of a response to that given by score.
setScoreAt(String, double) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
setScoreWeights(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
setScoreWeights(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
setScoreWeights(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setScoreWeights(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: A polytomous item is scored with two or more ordinal categories such as 0, 1, 2, 3 or 1, 2, 3, 4, 5.
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Set upper asymptote parameter to an existing value.
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setSlipping(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setSlipping(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set upper asymptote parameter to an existing value.
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setSlippingPrior(ItemParamPrior) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setSlippingPrior(ItemParamPrior) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: The guessing parameter standard error may be computed external to the class.
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setSlippingStdError(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setSlippingStdError(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: The slipping parameter standard error may be computed external to the class.
setSpecialDataCodes(SpecialDataCodes) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setSpecialDataCodes(SpecialDataCodes) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setStandardErrors(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setStandardErrors(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setStandardized(boolean) - Method in class com.itemanalysis.psychometrics.irt.equating.HaebaraMethod: Flag to standardize criterion function.
setStandardized(boolean) - Method in class com.itemanalysis.psychometrics.irt.equating.StockingLordMethod: Flag to standardize criterion function.
setStartValue(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setStepParameters() - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setStepParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setStepParameters(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setStepPriorAt(ItemParamPrior, int) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setStepPriorAt(ItemParamPrior, int) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setStepStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setStepStdError(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Sets the standard error for the step parameter estimates.
setStockingLordCritionType(EquatingCriterionType) - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
setStringFormat(int, TextTableColumnFormat.OutputAlignment) - Method in class com.itemanalysis.psychometrics.texttable.TextTableColumnFormat
setTerminateOnEvalImprovementNumOfEpoch(int) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
setTestItemOrder(int) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setThresholdParameters(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setThresholdParameters(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Sets the threshold parameters to particular values.
setThresholds(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup: Sets the array of threshold estimates.
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
setThresholdStdError(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
setThresholdStdError(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Set the threshold standard errors.
setTOL(double) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.Record
setToLogDeterministic(float[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
setToLogDeterministic(double[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
setUniformPointsAndWeights() - Method in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
setValue(double) - Method in class com.itemanalysis.psychometrics.kernel.UserSuppliedBandwidth
setVarcharSize(int) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
setVariableNameAt(int, VariableName) - Method in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
setVariableNameAt(int, String) - Method in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
setVariableNameAt(int, VariableName) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
setVariableNameAt(int, String) - Method in class com.itemanalysis.psychometrics.factoranalysis.ExploratoryFactorAnalysis
setVariableNameAt(int, VariableName) - Method in interface com.itemanalysis.psychometrics.factoranalysis.FactorMethod
setVerbose(boolean) - Method in class com.itemanalysis.psychometrics.irt.estimation.MarginalMaximumLikelihoodEstimation
showDetails(boolean) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin: Show detailed information about teh optimizer.
showDetails(boolean) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77: Show detailed information about teh optimizer.
shuffle(int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
shuffle(int[], Random) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
shutUp() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.Record
shutUp() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
sigLevelByApproxRand(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Computes the significance level by approximate randomization, using a default value of 1000 iterations.
sigLevelByApproxRand(double[], double[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Takes a pair of arrays, A and B, which represent corresponding outcomes of a pair of random variables: say, results for two different classifiers on a sequence of inputs.
sigLevelByApproxRand(int[], int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sigLevelByApproxRand(int[], int[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sigLevelByApproxRand(boolean[], boolean[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sigLevelByApproxRand(boolean[], boolean[], int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sigmoid(double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Compute the sigmoid function with mean zero.
sign_f77(double, double) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77: This method implements the FORTRAN sign (not sin) function.
significant(double) - Method in class com.itemanalysis.psychometrics.statistics.RobustZ
SijAt(int) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Sij is the frequency of responses in this score category or a higher category.
SimpleBinCalculation - Class in com.itemanalysis.psychometrics.histogram: An implementation of AbstractBinCalculation such that the user can provide the number of bins.
SimpleBinCalculation(int, double, double) - Constructor for class com.itemanalysis.psychometrics.histogram.SimpleBinCalculation
SimplePluginBandwidth - Class in com.itemanalysis.psychometrics.kernel: See Silverman (1986, p.
SimplePluginBandwidth(StandardDeviation) - Constructor for class com.itemanalysis.psychometrics.kernel.SimplePluginBandwidth
SimplePluginBandwidth(StandardDeviation, double) - Constructor for class com.itemanalysis.psychometrics.kernel.SimplePluginBandwidth
Sip() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Returns the raw item score.
size() - Method in class com.itemanalysis.psychometrics.cmh.CmhTableRow
size() - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.QNInfo
SloppyMath - Class in com.itemanalysis.psychometrics.optimization: The class SloppyMath contains methods for performing basic numeric operations.
smdConfidenceInterval(double) - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel: Computes 95% confidence interval for the standardized mean difference.
smdDifClass() - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
sndofd_f77(int, double[], Uncmin_methods, double[], double[][], double[], double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin: The sndofd_f77 method finds second order forward finite difference approximations to the Hessian.
sndofd_f77(int, double[], Uncmin_methods, double[], double[][], double[], double, double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77: The sndofd_f77 method finds second order forward finite difference approximations to the Hessian.
softmax(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
SpecialDataCodes - Class in com.itemanalysis.psychometrics.data
SpecialDataCodes() - Constructor for class com.itemanalysis.psychometrics.data.SpecialDataCodes
SpecialDataCodes(String) - Constructor for class com.itemanalysis.psychometrics.data.SpecialDataCodes: Creates an object using the variable name and code string.
SpjAt(int) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup: Spj is the sum of Sij over all categories.
spuriousCorrectedPearsonCorrelation() - Method in class com.itemanalysis.psychometrics.polycor.PolyserialPlugin: Correct pearson correlation for spuriousness due to including the studied item score Y in the computation of X values.
spuriousCorrectedValue() - Method in class com.itemanalysis.psychometrics.polycor.PolyserialPlugin: Correct polyserial correlation for spuriousness due to including the studied item score Y in the computation of X values.
SQRT_EPSILON - Static variable in class com.itemanalysis.psychometrics.measurement.MachineAccuracy
SQRT_SQRT_EPSILON - Static variable in class com.itemanalysis.psychometrics.measurement.MachineAccuracy
squaredIntegral() - Method in class com.itemanalysis.psychometrics.kernel.LeastSquaresCrossValidation
standardDeviation() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
standardDeviation() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
standardError(double[]) - Method in class com.itemanalysis.psychometrics.statistics.Bootstrap
standardErrorOfMean(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
StandardErrorOfMeasurement - Class in com.itemanalysis.psychometrics.reliability
StandardErrorOfMeasurement() - Constructor for class com.itemanalysis.psychometrics.reliability.StandardErrorOfMeasurement
standardize(boolean) - Method in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation: Uses current quadrature points and weights to compute the mean and standard deviation of the density, and then standardizes the distribution to have a mean of zero and a standard deviation of one.
standardize(boolean) - Method in interface com.itemanalysis.psychometrics.distribution.DistributionApproximation
standardize(boolean) - Method in class com.itemanalysis.psychometrics.histogram.Histogram: Uses current quadrature points and weights to compute the mean and standard deviation of the density, and tehn standardizes the distribution to have a mean of zero and a standard deviation of one.
standardize(boolean) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity: Uses current quadrature points and weights to compute the mean and standard deviation of the density, and tehn standardizes the distribution to have a mean of zero and a standard deviation of one.
standardize(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Standardize values in this array, i.e., subtract the mean and divide by the standard deviation.
standardizedHaebara(boolean) - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
standardizedStockingLord(boolean) - Method in class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
start(double, double[]) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.Record
start(double, double[], double[]) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer.Record
StartingValues - Class in com.itemanalysis.psychometrics.irt.estimation: Computes starting values for binary item response models.
StartingValues(ItemResponseVector[], ItemResponseModel[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.StartingValues: Default constructor takes an array of item response vectors and an array of item response models.
stdError(double[], double[][]) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood: Computes the standard errors of the item parameter estimates.
stdError(ItemResponseModel) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood
stdev(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
step - Variable in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
step - Variable in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
stepPrior - Variable in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
stepStdError - Variable in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
StochasticCalculateMethods - Enum in com.itemanalysis.psychometrics.optimization: This enumeratin was created to organize the selection of different methods for stochastic calculations.
StockingLordMethod - Class in com.itemanalysis.psychometrics.irt.equating
StockingLordMethod(LinkedHashMap<String, ItemResponseModel>, LinkedHashMap<String, ItemResponseModel>, DistributionApproximation, DistributionApproximation, EquatingCriterionType) - Constructor for class com.itemanalysis.psychometrics.irt.equating.StockingLordMethod
StopWatch - Class in com.itemanalysis.psychometrics.tools: The StopWatch class provide date and time functions including an elapsed time function that provides calculations to the milisecond.
StopWatch() - Constructor for class com.itemanalysis.psychometrics.tools.StopWatch
StorelessDescriptiveStatistics - Class in com.itemanalysis.psychometrics.statistics
StorelessDescriptiveStatistics() - Constructor for class com.itemanalysis.psychometrics.statistics.StorelessDescriptiveStatistics
stringIterator() - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
stringIterator() - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary
stringIterator() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
stringResponseMap - Variable in class com.itemanalysis.psychometrics.measurement.AbstractItemResponseSummary
stringScoreMap - Variable in class com.itemanalysis.psychometrics.measurement.AbstractItemResponseSummary
SturgesBinCalculation - Class in com.itemanalysis.psychometrics.histogram: Sturges' method for computing the number of bins.
SturgesBinCalculation(double, double, double) - Constructor for class com.itemanalysis.psychometrics.histogram.SturgesBinCalculation
subArray(int[], int, int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sum(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the sum of an array of numbers.
sum(double[], int, int) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath: Returns the sum of the portion of an array of numbers between fromIndex, inclusive, and toIndex, exclusive.
sum(int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sum(float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sum(int[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
summarize(double[], int[]) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
summarize() - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
summarize() - Method in class com.itemanalysis.psychometrics.polycor.PolyserialLogLikelihoodTwoStep
summarizeData(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: Summarizes data into frequency counts.
sumMatrix(RealMatrix) - Static method in class com.itemanalysis.psychometrics.factoranalysis.MatrixUtils
sumOfScores() - Method in class com.itemanalysis.psychometrics.cmh.CmhTable: Computes the marginal sum of scores.
sumOfScores() - Method in class com.itemanalysis.psychometrics.cmh.CmhTableRow: Computes the sum of scores for those values in columns.
sumOfSquaredScores() - Method in class com.itemanalysis.psychometrics.cmh.CmhTable: Computes the marginal sum of squared scores.
sumScore - Variable in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: Sum of the response vector, excluding missing responses.
sumsOfSquares - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
sumSquared(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
sumSquaredError(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
suppressTestPrompt(boolean) - Method in class com.itemanalysis.psychometrics.optimization.QNMinimizer
SurpriseConvergence(String) - Constructor for class com.itemanalysis.psychometrics.optimization.QNMinimizer.SurpriseConvergence

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