- n - Variable in class com.itemanalysis.psychometrics.histogram.AbstractBinCalculation
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Sample size.
- N - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- N - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
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- name - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
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- name - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
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- nameChanged() - Method in class com.itemanalysis.psychometrics.data.VariableName
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- nameForDatabase() - Method in class com.itemanalysis.psychometrics.data.VariableName
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Leading and trailing "x" added for database security and prevent use of reserved words
- ncat - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
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- ncat - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
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- ncatM1 - Variable in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
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- nChooseK(int, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
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Computes n choose k in an efficient way.
- ncol - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- nearestNonZero(double) - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemParamPrior
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- nearestNonZero(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta
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- nearestNonZero(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta4
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If the density of x is zero then return the point nearest x that has a non-zero density.
- nearestNonZero(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorLogNormal
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If density of x is zero (x <= 0) then return small slightly greater than zero that has a non-zero density
- nearestNonZero(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorNormal
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Empty method
- next() - Method in class com.itemanalysis.psychometrics.irt.model.IrmCollection.GroupModelIterator
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- nFactors - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
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- nItems - Variable in class com.itemanalysis.psychometrics.irt.estimation.ItemResponseVector
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Number of items in the response vector
- nItems - Variable in class com.itemanalysis.psychometrics.reliability.AbstractScoreReliability
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- NonparametricIccBandwidth - Class in com.itemanalysis.psychometrics.kernel
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Bandwidth for nonparametric item characteristic curves via KernelRegression.
- NonparametricIccBandwidth(double, double) - Constructor for class com.itemanalysis.psychometrics.kernel.NonparametricIccBandwidth
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
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- nonZeroPrior(double[]) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
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- nonZeroPrior(double[]) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
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If the prior density for a parameter is zero, adjust parameter to the nearest non zero value.
- norm(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes 2-norm of vector.
- norm(float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes 2-norm of vector.
- norm - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- norm - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolyserialCorrelation
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- norm_1(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes 1-norm of vector.
- norm_1(float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes 1-norm of vector.
- norm_inf(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes inf-norm of vector.
- norm_inf(float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Computes inf-norm of vector.
- normal - Variable in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
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- NormalDistributionApproximation - Class in com.itemanalysis.psychometrics.distribution
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An immutable object for creating evaluation points and associated density values from a normal distribution.
- NormalDistributionApproximation(double, double, int) - Constructor for class com.itemanalysis.psychometrics.distribution.NormalDistributionApproximation
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Creates a numerical approximation to the standard normal distribution.
- NormalDistributionApproximation(double, double, double, double, int) - Constructor for class com.itemanalysis.psychometrics.distribution.NormalDistributionApproximation
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Creates a numerical approximation to a normal distribution with the specified mean and standard deviation.
- normalize(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Makes the values in this array sum to 1.0.
- normalize(float[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Makes the values in this array sum to 1.0.
- NormalizedScore - Class in com.itemanalysis.psychometrics.scaling
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- NormalizedScore() - Constructor for class com.itemanalysis.psychometrics.scaling.NormalizedScore
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- normalizedScoreTable(NormalizedScore, ScoreBounds, boolean) - Method in class com.itemanalysis.psychometrics.scaling.ScoreTable
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- NormalScores - Class in com.itemanalysis.psychometrics.statistics
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- NormalScores() - Constructor for class com.itemanalysis.psychometrics.statistics.NormalScores
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- nParam - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
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- nrow - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- numberOfBins() - Method in interface com.itemanalysis.psychometrics.histogram.BinCalculation
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Get the number of histogram bins.
- numberOfBins() - Method in class com.itemanalysis.psychometrics.histogram.FreedmanDiaconisBinCalculation
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Gets the number of bins calculated by the Freedman-Diaconis method.
- numberOfBins() - Method in class com.itemanalysis.psychometrics.histogram.ScottBinCalculation
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- numberOfBins() - Method in class com.itemanalysis.psychometrics.histogram.SimpleBinCalculation
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- numberOfBins() - Method in class com.itemanalysis.psychometrics.histogram.SturgesBinCalculation
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Gets the number of bins as computed by Sturges' method.
- numberOfBins - Variable in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
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- numberOfCategories - Variable in class com.itemanalysis.psychometrics.irt.estimation.AbstractItemFitStatistic
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- numberOfCategories() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItem
-
Number of response categories
- numberOfCategories() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalItemSummary
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- numberOfCategories() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
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Gets the number of response options.
- numberOfCategories() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
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- numberOfGroups() - Method in interface com.itemanalysis.psychometrics.mixture.MixtureModel
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- numberOfGroups() - Method in class com.itemanalysis.psychometrics.mixture.MvNormalMixtureModel
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- numberOfItems() - Method in class com.itemanalysis.psychometrics.measurement.ClassicalTestSummary
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- numberOfItems() - Method in class com.itemanalysis.psychometrics.measurement.TestSummary
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- numberOfNonexremeItems() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
-
An extreme iem is one in which all examinees with obtain the lowest possible item score or one in which
all examinee obtain the highest possible item score.
- numberOfNonextremePeople() - Method in class com.itemanalysis.psychometrics.irt.estimation.JointMaximumLikelihoodEstimation
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An extreme person is one that obtains the minimum possible test score or the maximum possible test score.
- numberOfPoints - Variable in class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation
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- numberOfScoreLevels() - Method in class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
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Gets the number of score levels.
- numberOfScoreLevels() - Method in interface com.itemanalysis.psychometrics.measurement.ItemScoring
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- numberOfStrata() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityStatistics
-
Number of distinct strata that are possible with the given estimates.
- NumericItemResponseSummary - Class in com.itemanalysis.psychometrics.measurement
-
Summarizes item responses that are numeric.
- NumericItemResponseSummary(VariableName) - Constructor for class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary
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- numRows(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
-
- nVariables - Variable in class com.itemanalysis.psychometrics.factoranalysis.AbstractFactorMethod
-