com.itemanalysis.psychometrics.measurement

Class ClassicalItem

java.lang.Object

com.itemanalysis.psychometrics.measurement.ClassicalItem

public class ClassicalItem
extends java.lang.Object

This is the main class for conducting a classical item analysis. It scores the item and incrementally updates the item statistics. Output includes item difficulty and discrimination. It computes statistic for the entire item ("overall") and optionally for each possible response option.

Author:

J. Patrick Meyer

Constructor Summary

Constructors

Constructor and Description
ClassicalItem(VariableAttributes variableAttributes, boolean biasCorrection, boolean allCategories, boolean pearson, boolean computeDIndex)

Method Summary

Modifier and Type	Method and Description
java.util.Iterator<java.lang.Object>	categoryIterator() Iterator for the catgory objects
double	factorLoadingApproximation() Deprecated.
double	getDifficulty() Classical item difficulty estimate
double	getDifficultyAt(java.lang.Object index) Return the proportion selecting a particular response option.
double	getDindex()
double	getDindexLower()
double	getDindexUpper()
double	getDiscrimination() Classical item discrimination estimate (i.e.
double	getDiscriminationAt(java.lang.Object index) Option-total score correlation.
VariableName	getName() Name of item
double	getStdDev() Item standard deviation
double	getStdDevAt(java.lang.Object index) Standard deviation for the proportion of examinees endorsing teh response option.
void	increment(double sumScore, java.lang.Object response)
void	increment(RawScore rawScore, java.lang.Object response) Incrementally update item statistics
void	incrementDindex(java.lang.Object response, double testScore, double lowerCut, double upperCut)
boolean	isContinuous()
int	numberOfCategories() Number of response categories
java.lang.String	printHeader() Header for the item analysis output.
java.lang.String	toString() Provide all requested statistics for the item.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

ClassicalItem

public ClassicalItem(VariableAttributes variableAttributes,
                     boolean biasCorrection,
                     boolean allCategories,
                     boolean pearson,
                     boolean computeDIndex)

Method Detail

isContinuous

public boolean isContinuous()

increment

public void increment(RawScore rawScore,
                      java.lang.Object response)

Incrementally update item statistics

Parameters:

rawScore - sum score for the entire test

response - observed item response (not the score value)

increment

public void increment(double sumScore,
                      java.lang.Object response)

incrementDindex

public void incrementDindex(java.lang.Object response,
                            double testScore,
                            double lowerCut,
                            double upperCut)

factorLoadingApproximation

@Deprecated
public double factorLoadingApproximation()

Deprecated.

Principal Factor Analysis Centroid method approximaiton. This method provides starting values for confirmatory factor analysis factor loadings.

Returns:

an approximation to teh factor loading

numberOfCategories

public int numberOfCategories()

Number of response categories

Returns:

the number of response categories

getName

public VariableName getName()

Name of item

Returns:

name of the item

getDifficulty

public double getDifficulty()

Classical item difficulty estimate

Returns:

item difficulty

getStdDev

public double getStdDev()

Item standard deviation

Returns:

item standard deviation

getDiscrimination

public double getDiscrimination()

Classical item discrimination estimate (i.e. item-total correlation)

Returns:

item discrimination

getDindexLower

public double getDindexLower()

getDindexUpper

public double getDindexUpper()

getDindex

public double getDindex()

getDifficultyAt

public double getDifficultyAt(java.lang.Object index)

Return the proportion selecting a particular response option.

Parameters:

index - value of teh response option

Returns:

proportion endorsing the resposne option

getStdDevAt

public double getStdDevAt(java.lang.Object index)

Standard deviation for the proportion of examinees endorsing teh response option.

Parameters:

index - value of teh response option

Returns:

standard deviation for the proportion of examinees endorsing teh response option

getDiscriminationAt

public double getDiscriminationAt(java.lang.Object index)

Option-total score correlation. For teh correct answer this value is the item discrimination. For teh distractors it is the distractor total correlation.

Parameters:

index - value of teh response option

Returns:

option-total correlation

categoryIterator

public java.util.Iterator<java.lang.Object> categoryIterator()

Iterator for the catgory objects

Returns:

iterator for the categories

printHeader

public java.lang.String printHeader()

Header for the item analysis output. Usually only called for the first item.

Returns:

output header

toString

public java.lang.String toString()

Provide all requested statistics for the item. This output aligns with the printHeader() method.

Overrides:

toString in class java.lang.Object

Returns:

string output