I-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

I

iclbic() - Method in class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
IdentityMatrix - Class in com.itemanalysis.psychometrics.statistics
IdentityMatrix(int) - Constructor for class com.itemanalysis.psychometrics.statistics.IdentityMatrix
IdentityVector - Class in com.itemanalysis.psychometrics.statistics
IdentityVector(int) - Constructor for class com.itemanalysis.psychometrics.statistics.IdentityVector
inBin(double) - Method in class com.itemanalysis.psychometrics.histogram.Bin: Tests whether a value belongs to this bin.
increment(Object, Double) - Method in class com.itemanalysis.psychometrics.cmh.CmhTable
increment(double, String, double) - Method in class com.itemanalysis.psychometrics.cmh.CochranMantelHaenszel
increment(double, double) - Method in class com.itemanalysis.psychometrics.distribution.UserSuppliedDistributionApproximation: Deprecated.

Increment the array of evaluation points and weights with the provided values.
increment(double) - Method in class com.itemanalysis.psychometrics.distribution.UserSuppliedDistributionApproximation: Deprecated.

An evaluation points.
increment(double) - Method in class com.itemanalysis.psychometrics.histogram.AbstractBinCalculation: Update the summary statistics with a new value.
increment(double) - Method in class com.itemanalysis.psychometrics.histogram.Bin: Incrementally count a value as belonging to this bin if it fits within the bounds.
increment(double, double) - Method in class com.itemanalysis.psychometrics.histogram.Bin: Incrementally count a value as belonging to this bin if it fits within the bounds.
increment(double) - Method in class com.itemanalysis.psychometrics.histogram.Cut
increment(double) - Method in class com.itemanalysis.psychometrics.histogram.Histogram: Incrementally counts the number of observations in each bin.
increment(double, double) - Method in class com.itemanalysis.psychometrics.histogram.Histogram
increment(EstepEstimates) - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepEstimates
increment(double, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitG2: Increment fit statistic.
increment(double, int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitG2
increment(int, int) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitSX2: Increment fit statistic assuming there is a table row for each possible summed score.
increment(int, int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitSX2
increment(byte) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Count frequency of responses in each score category.
increment(double, double, ItemResponseModel) - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschCategoryFitStatistic
increment(ItemResponseModel, double, byte) - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschFitStatistics
increment(double, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityStatistics: An incremental update to the scale quality statistics.
increment(double) - Method in class com.itemanalysis.psychometrics.kernel.KernelDensity: Incremental computation of the density.
increment(double, double) - Method in class com.itemanalysis.psychometrics.kernel.KernelRegression: Increment the estimate by x and y
increment(double, double, double) - Method in class com.itemanalysis.psychometrics.kernel.KernelRegression
increment(Object, double) - Method in class com.itemanalysis.psychometrics.measurement.CategoryResponseSummary: Use this incremental update for each response option.
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.CategoryResponseSummary: Use this incremental update if the item is continuous or the response is already scored.
increment(RawScore, Object) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem: Incrementally update item statistics
increment(double, Object) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemStatistics: Incrementally update the item statistics
increment(String, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
increment(double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
increment(double, String) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, String, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, int) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, int, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
increment(double, String) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(double, String, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(double, int) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(double, int, double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
increment(String) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(String, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(int) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(int, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(double, double) - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.ItemStats: Incrementally update the item statistics
increment(double, Object) - Method in class com.itemanalysis.psychometrics.measurement.KernelRegressionCategories
increment(double, Object) - Method in class com.itemanalysis.psychometrics.measurement.KernelRegressionItem
increment(String) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by one.
increment(String, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by an amount equal to freqWeight.
increment(int) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by one.
increment(int, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by an amount equal to freqWeight.
increment(double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by one.
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary: Increment frequency count of a response by an amount equal to freqWeight.
increment(RawScore) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
increment(double) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
increment(int) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
increment(int, double) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
increment(double) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
increment(double, double) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
increment(String) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: A unit increment of the item reponse count.
increment(String, double) - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary: An increment of the item response count that uses a frequency weight.
increment(int, int) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
increment(char, char) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
increment(long, long) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
increment(double, int) - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
increment(Double, Double) - Method in class com.itemanalysis.psychometrics.polycor.Covariance: Update formula for recursive on-line (i.e.
increment(int, int, Double, Double) - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix: Increment values in the matrix.
increment(int, int, double, double) - Method in class com.itemanalysis.psychometrics.polycor.MixedCorrelationMatrix: Increments the appropriate correlation object.
increment(Double, Double) - Method in class com.itemanalysis.psychometrics.polycor.PearsonCorrelation
increment(double, int) - Method in class com.itemanalysis.psychometrics.polycor.PolyserialPlugin
increment(Double) - Method in class com.itemanalysis.psychometrics.reliability.CSEMList: Increment for each true score provided.
increment(Double) - Method in class com.itemanalysis.psychometrics.scaling.RawScore
increment(Double, Double) - Method in class com.itemanalysis.psychometrics.scaling.ScoreBounds: increment according to item scores
increment(double) - Method in class com.itemanalysis.psychometrics.statistics.StorelessDescriptiveStatistics
incremental - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
incremental - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
incrementByItemScores(ArrayList<VariableAttributes>) - Method in class com.itemanalysis.psychometrics.scaling.ScoreBounds
incrementDindex(Object, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.CategoryResponseSummary
incrementDindex(double, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.CategoryResponseSummary: This method is called when computing teh D-index for the overall item.
incrementDindex(Object, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem
incrementDindex(double, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemStatistics: The D index must be incremented in a second loop after test scores have been computed and percentiles computed.
incrementDindex(String, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
incrementDindex(double, double, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ItemStats: The D index must be incremented in a second loop after test scores have been computed and percentiles computed.
incrementFitStatistics(ItemResponseModel, double, byte) - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup: Category fit statistics are incrementally updated with repeated calls to this method.
incrementLoglikelihood(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepEstimates
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Mean/mean linking coefficients are computed from the mean item difficulty and mean item discrimination.
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Mean/mean linking coefficients are computed from the mean item difficulty and mean item discrimination.
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
incrementMeanMean(Mean, Mean) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
incrementMeanMean(Mean, Mean) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Mean/mean linking coefficients are computed from teh mean item difficulty and mean item discrimination.
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Mean/sigma linking coefficients are computed from the mean and standard deviation of item difficulty.
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL: Mean/sigma linking coefficients are computed from the mean and standard deviation of item difficulty.
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
incrementMeanSigma(Mean, StandardDeviation) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
incrementMeanSigma(Mean, StandardDeviation) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Mean/sigma linking coefficients are computed from teh mean and standard deviation of item difficulty.
incrementNt(int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepEstimates
incrementPartTestReliability(int, int, double, double) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
incrementPartTestReliability(RawScore) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
incrementReliability(int, int, double, double) - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
incrementReliability(int, int, double, double) - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
incrementResponseVector(Integer, Object, Double) - Method in class com.itemanalysis.psychometrics.scaling.RawScore: For holding an examinee's vector of item responses.
incrementRjkt(int, int, int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepEstimates
incrementRjkt(int, int, double) - Method in class com.itemanalysis.psychometrics.irt.estimation.EstepItemEstimates
incrementSubScaleScore(String, double) - Method in class com.itemanalysis.psychometrics.scaling.RawScore
indexOf(int, int[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
InformationFitCriteria - Class in com.itemanalysis.psychometrics.mixture
InformationFitCriteria(MixtureModel) - Constructor for class com.itemanalysis.psychometrics.mixture.InformationFitCriteria
InformationFitCriteria.FitCriterion - Enum in com.itemanalysis.psychometrics.mixture
initialize() - Method in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
initialize() - Method in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
initializeCategories() - Method in class com.itemanalysis.psychometrics.measurement.KernelRegressionCategories
initializeCategories() - Method in class com.itemanalysis.psychometrics.measurement.KernelRegressionItem
initializeExpectedFrequencies() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemFitG2
innerProduct(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
innerProduct(float[], float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
interpolatorUpdateNeeded - Variable in class com.itemanalysis.psychometrics.histogram.Histogram
interpolatorUpdateNeeded - Variable in class com.itemanalysis.psychometrics.kernel.KernelDensity
intPow(int, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Exponentiation like we learned in grade school: multiply b by itself e times.
intPow(float, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Exponentiation like we learned in grade school: multiply b by itself e times.
intPow(double, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Exponentiation like we learned in grade school: multiply b by itself e times.
intValue() - Method in class com.itemanalysis.psychometrics.scaling.RawScore
InvalidElementException(String) - Constructor for exception com.itemanalysis.psychometrics.optimization.ArrayMath.InvalidElementException
irm - Variable in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
Irm3PL - Class in com.itemanalysis.psychometrics.irt.model: An implementation of AbstractItemResponseModel that allows for the three-parameter logistic (3PL) model, two-parameter logistic (2PL) model, one-parameter logistic (1PL) model, and the Rasch model.
Irm3PL(double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.Irm3PL: Constructor for three parameter logistic model
Irm3PL(double, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.Irm3PL: Constructor for two parameter logistic model.
Irm3PL(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.Irm3PL: Constructor for one parameter logistic model
Irm4PL - Class in com.itemanalysis.psychometrics.irt.model: Four parameter logistic model.
Irm4PL(double, double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.Irm4PL: Constructor for four parameter logistic model
IrmBinary - Class in com.itemanalysis.psychometrics.irt.model: This class provides a cleaner interface to the Irm3PL class.
IrmBinary(double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmBinary
IrmBinary(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmBinary
IrmBinary(double, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmBinary
IrmCollection - Class in com.itemanalysis.psychometrics.irt.model: This class represents the item response models for an entire test or collection of item response models.
IrmCollection() - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmCollection
IrmCollection.GroupModelIterator - Class in com.itemanalysis.psychometrics.irt.model: A class that iterates over the item response model objects for a specific group of items.
IrmGPCM - Class in com.itemanalysis.psychometrics.irt.model: This version of the Generalized Partial Credit Model (GPCM) uses a discrimination parameter and two or more step parameters.
IrmGPCM(double, double[], double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmGPCM: Default constructor
IrmGPCM2 - Class in com.itemanalysis.psychometrics.irt.model: This version of the Generalized Partial Credit Model (GPCM) uses a discrimination parameter, a difficulty parameter (b), and one or more threshold parameters.
IrmGPCM2(double, double, double[], double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmGPCM2: Default constructor
IrmGRM - Class in com.itemanalysis.psychometrics.irt.model: Samejima's graded response model.
IrmGRM(double, double[], double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmGRM: Default constructor
IrmPCM - Class in com.itemanalysis.psychometrics.irt.model: This version of the Partial Credit Model (GPCM) uses a difficulty parameter (b), and one or more threshold parameters.
IrmPCM(double, double[], double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmPCM: Default constructor
IrmPCM2 - Class in com.itemanalysis.psychometrics.irt.model: Class that implements the partial credit model.
IrmPCM2(double[], double) - Constructor for class com.itemanalysis.psychometrics.irt.model.IrmPCM2: Default constructor for an m category item.
IrmType - Enum in com.itemanalysis.psychometrics.irt.model
IrtEstimation - Interface in com.itemanalysis.psychometrics.irt.estimation: Interface for IRT estimation.
IrtExaminee - Class in com.itemanalysis.psychometrics.irt.estimation: This class holds an item responseVector vector for an examinee and stores a count of the number of examinees with the same responseVector vector.
IrtExaminee(String, ItemResponseModel[], ItemResponseVector) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
IrtExaminee(ItemResponseModel[], ItemResponseVector) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
IrtExaminee(String, ItemResponseModel[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee: this constructor allows a single instance to be used for estimating ability for multiple people by calling setResponseVector() prior to calling for amethod to compute ability.
IrtExaminee(ItemResponseModel[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee: this constructor allows a single instance to be used for estimating ability for multiple people by calling setResponseVector() prior to calling for amethod to compute ability.
IrtExaminee(ArrayList<ItemResponseModel>) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
IrtExaminee(LinkedHashMap<VariableName, ItemResponseModel>) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
IrtObservedScoreCollection - Class in com.itemanalysis.psychometrics.irt.estimation: This class computes the IRT observed score distribution for an entire test.
IrtObservedScoreCollection(ItemResponseModel[], DistributionApproximation) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtObservedScoreCollection
IrtObservedScoreDistribution - Class in com.itemanalysis.psychometrics.irt.estimation: This class computes the distribution of summed scores for a given set of item response models.
IrtObservedScoreDistribution(ItemResponseModel[], DistributionApproximation) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IrtObservedScoreDistribution
IrtScaleLinking - Class in com.itemanalysis.psychometrics.irt.equating
IrtScaleLinking(LinkedHashMap<String, ItemResponseModel>, LinkedHashMap<String, ItemResponseModel>, DistributionApproximation, DistributionApproximation, boolean) - Constructor for class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
IrtScaleLinking(LinkedHashMap<String, ItemResponseModel>, LinkedHashMap<String, ItemResponseModel>, DistributionApproximation, DistributionApproximation) - Constructor for class com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking
IrtTrueScoreEquating - Class in com.itemanalysis.psychometrics.irt.equating
IrtTrueScoreEquating(LinkedHashMap<String, ItemResponseModel>, LinkedHashMap<String, ItemResponseModel>) - Constructor for class com.itemanalysis.psychometrics.irt.equating.IrtTrueScoreEquating
isamax_f77(int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77: This method finds the index of the element of a vector that has the maximum absolute value.
isCloseTo(double, double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
isContinuous() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem
isContinuous(boolean) - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
isContinuous() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
isContinuous(boolean) - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
isDangerous(double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Returns true if the argument is a "dangerous" double to have around, namely one that is infinite, NaN or zero.
isExtreme() - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
isExtreme() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: A boolean method that returns true if the item is an extreme minimum or and extreme maximum.
isExtremeMaximum() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: An extreme maximum item score is one in which the raw item score equals the minimum possible raw item score.
isExtremeMinimum() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: An extreme minimum item score is one in which the raw item score equals the maximum possible raw item score.
isFixed - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
isFixed() - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
isFixed - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
isFixed() - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
isFixed() - 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.
isFixed() - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup
isMissing(String) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isMissing(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isMissing(double) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isMissing(int) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isMissing(String) - Method in class com.itemanalysis.psychometrics.data.VariableAttributes
isNotReached(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isOmitted(Object) - Method in class com.itemanalysis.psychometrics.data.SpecialDataCodes
isVeryDangerous(double) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath: Returns true if the argument is a "very dangerous" double to have around, namely one that is infinite or NaN.
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.CoefficientAlpha: Computes reliability with each item omitted in turn.
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.FeldtBrennan: Computes reliability with each item omitted in turn.
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.FeldtGilmer: Computes reliability with each item omitted in turn.
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.GuttmanLambda: Computes reliability with each item omitted in turn.
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.KR21
itemDeletedReliability() - Method in class com.itemanalysis.psychometrics.reliability.RajuBeta
itemDeletedReliability() - Method in interface com.itemanalysis.psychometrics.reliability.ScoreReliability: An array of reliability estimates without the item indexed by the position in the array.
itemDeletedString() - Method in class com.itemanalysis.psychometrics.reliability.ReliabilitySummary
ItemFitG2 - Class in com.itemanalysis.psychometrics.irt.estimation
ItemFitG2(ItemResponseModel, Cut, int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemFitG2: This constructor is designed for the case where the number of table rows and the boundaries are specified in thetaCut.
ItemFitStatistic - Interface in com.itemanalysis.psychometrics.irt.estimation
ItemFitSX2 - Class in com.itemanalysis.psychometrics.irt.estimation: Computes the generalized S-X2 statistic developed by: Kang, T., and Chen, T., T.
ItemFitSX2(IrtObservedScoreDistribution, IrtObservedScoreDistribution, ItemResponseModel, int, int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemFitSX2
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL: Computes the item information function at theta.
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM: From Ostini and Nering but needs checking.
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
itemInformationAt(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
itemInformationAt(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel: Computes the item information function at theta.
ItemLogLikelihood - Class in com.itemanalysis.psychometrics.irt.estimation: This class contains contains methods for the loglikelihood function for an item, which is the value of the objective function that is being minimized in the Mstep to obtain the maximum likelihood or Bayes modal estimates.
ItemLogLikelihood() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood
ItemLogLikelihoodFunction - Interface in com.itemanalysis.psychometrics.irt.estimation
ItemParamPrior - Interface in com.itemanalysis.psychometrics.irt.estimation
ItemParamPriorBeta - Class in com.itemanalysis.psychometrics.irt.estimation
ItemParamPriorBeta(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta
ItemParamPriorBeta4 - Class in com.itemanalysis.psychometrics.irt.estimation: Implementation of an ItemParamPrior for the Beta4 distribution.
ItemParamPriorBeta4() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta4
ItemParamPriorBeta4(double, double, double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta4
ItemParamPriorLogNormal - Class in com.itemanalysis.psychometrics.irt.estimation: Implementation of an ItemParamPrior for the LogNormal distribution.
ItemParamPriorLogNormal() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorLogNormal: Constructor for the standard lognormal distribution
ItemParamPriorLogNormal(double[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorLogNormal: Constructor takes an array as the input parameters.
ItemParamPriorLogNormal(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorLogNormal: Constructor taking the mean and standard deviation as arguments.
ItemParamPriorNormal - Class in com.itemanalysis.psychometrics.irt.estimation: Implementation of an ItemParamPrior for the Normal distribution.
ItemParamPriorNormal() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorNormal: Constructor for the standard normal distribution
ItemParamPriorNormal(double[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorNormal: A constructor for an array of parameters.
ItemParamPriorNormal(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorNormal
ItemPolytomous - Class in com.itemanalysis.psychometrics.irt.estimation
ItemPolytomous() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemPolytomous
itemProx() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation: Computes PROX difficulty estimates for item difficulty.
ItemResponseComparator() - Constructor for class com.itemanalysis.psychometrics.measurement.DefaultItemScoring.ItemResponseComparator
ItemResponseFileSummary - Class in com.itemanalysis.psychometrics.irt.estimation
ItemResponseFileSummary() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseFileSummary
ItemResponseModel - Interface in com.itemanalysis.psychometrics.irt.model: An item response model describes the relationship between the probability of a score category and person ability (i.e.
ItemResponseModelWithGradient - Interface in com.itemanalysis.psychometrics.irt.model
ItemResponseSimulator - Class in com.itemanalysis.psychometrics.irt.estimation: ItemResponseSimulator.java creates data that contain item responses.
ItemResponseSimulator(double[], ItemResponseModel[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSimulator: Allows users to provide their own array of examinee ability values and item response models.
ItemResponseSimulator(int, ItemResponseModel[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSimulator: Allows users to specify the number of examinee ability parameters that will be drawn from a standrad normal distribution.
ItemResponseSummary - Class in com.itemanalysis.psychometrics.irt.estimation: This class is used to count and store item response frequencies for JointMaximumLikelihoodEstimation.
ItemResponseSummary(VariableName, String, double, byte[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary: Create an item response summary object with information about the variable.
ItemResponseSummary(VariableName, double, byte[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary
ItemResponseSummary(VariableName, byte[]) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseSummary
ItemResponseSummary - Interface in com.itemanalysis.psychometrics.measurement
ItemResponseVector - Class in com.itemanalysis.psychometrics.irt.estimation: A class for storing the item response vector and frequency counts.
ItemResponseVector(String, byte[], VariableName[], double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
ItemResponseVector(String, byte[], ArrayList<VariableName>, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
ItemResponseVector(String, ArrayList<Byte>, ArrayList<VariableName>, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
ItemResponseVector(String, byte[], double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: A constructor that is designed for storing all response vectors during MML estimation.
ItemResponseVector(byte[], double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: A constructor that is designed for storing all response vectors during MML estimation.
ItemResponseVector(String, int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: A constructor that takes an argument for the group ID and number of items.
ItemResponseVector(int) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector: A constructor that only requires the number of items.
ItemScoring - Interface in com.itemanalysis.psychometrics.measurement
ItemStats - Class in com.itemanalysis.psychometrics.measurement: This class computes statistics for individual item response options.
ItemStats(Object, boolean, boolean, boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.ItemStats
ItemStats(Object, boolean, boolean, boolean, boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.ItemStats
IterationRecord - Class in com.itemanalysis.psychometrics.irt.estimation: A class for storing the maximum change in logits and the log-likelihood at each iteration.
IterationRecord(double, double) - Constructor for class com.itemanalysis.psychometrics.irt.estimation.IterationRecord: Each instance stores information about the iteration.
iterator() - Method in class com.itemanalysis.psychometrics.histogram.Histogram: Gets the iterator for the array list of bin objects.
iterator() - Method in class com.itemanalysis.psychometrics.irt.model.IrmCollection: An iterator for all item response models in this collection (i.e.
iterator() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
iterator() - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
iteratorAt(double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalNumericItemResponseSummary
iteratorAt(double) - Method in class com.itemanalysis.psychometrics.measurement.ConditionalTextItemResponseSummary
itertaions() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel

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