etirm::ItemNR< D > Class Template Reference

Class, derived from Item, to maintain information calculated for an Item object in the E-step so that it can be used in the M-step to estimate item parameters. More...

#include <ItemNR.h>

Inheritance diagram for etirm::ItemNR< D >:

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Collaboration diagram for etirm::ItemNR< D >:

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List of all members.

Public Types
typedef RealMatrix::row_iterator	r_iterator
	Type iterator over responses of an item.
typedef RealVector::iterator	n_iterator
	Type iterator over number of examinees who responded to an item.
typedef D::point_iterator	point_iterator
	Type iterator over quadrature points.
Public Member Functions
	ItemNR (int nparam, int index, int respCat, D *dist=0)
	Constructor.
virtual	~ItemNR ()
	Destructor.
r_iterator	RVector (Response resp, int group=1)
	Returns iterator to first element of row of mR corresponding to response "resp" for examinee group "group" (where the first examinee group is group 1).
n_iterator	NVector (int group=1)
	Returns iterator to first element of mN for examinee group "group" (where the first examinee group is group 1).
void	SetLatentVarPoints (int n, point_iterator points)
	Assigns values associated with discrete latent variable categories.
point_iterator	GetLatentVarPoints (int group=1)
	Returns iterator over quadrature points.
int	NumLatentVarCat ()
	Returns number of discrete latent variable categories.
void	InitializeNR ()
	Initializes elements of mR and mN to zero.
virtual double	f_to_minimize (RealVector &p)=0
	Function to maximize in M-step.
virtual void	gradient (RealVector &p, RealVector &g)=0
	Computes gradient of function to maximize in M-step.
virtual void	hessian (RealVector &x, RealMatrix &h)=0
	Computes hessian of function to maximize in M-step.
virtual int	HasAnalyticGradient () const =0
	Function to indicate that the algebraic gradient of the item (ICCDeriv1) is defined.
virtual int	HasAnalyticHessian () const =0
	Function to indicate that the algebraic hessian of the item (ICCDeriv2) is defined.
virtual int	ValidParameters (const RealVector &p, bool ignorePriors=false) const
	Returns 1 if all parameters have a non-zero prior density, or 0 otherwise.
int	dim () const
	Number of item parameters.
Protected Attributes
D *	mLatentDist
	Latent variable distribution used to determine discrete categories on the latent variable.
RealMatrix *	mR
	Expected number of respondents in each latent variable category who took this item and gave the i-th response.
RealVector *	mN
	Expected number of examinees who took this item in each latent variable category.
int	mNumLatentVarCat
	Number of latent variable categories.

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Detailed Description

template<class D>
class etirm::ItemNR< D >

Class, derived from Item, to maintain information calculated for an Item object in the E-step so that it can be used in the M-step to estimate item parameters.

Information stored from the E-step includes the expected number of examinees in each category of the discrete latent variable of those that took the item (these usually are denoted by the letter "n"), and for each item response the expected number of examinees in each category of the discrete latent variable who gave that item response of those examinees who took the item (these usually are denoted by the letter "r").

Template Parameters

Parameters:

D

Class for discrete latent variable distribution.

Definition at line 57 of file ItemNR.h.

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Member Typedef Documentation

template<class D>

typedef RealMatrix::row_iterator etirm::ItemNR< D >::r_iterator

Type iterator over responses of an item.

Definition at line 63 of file ItemNR.h.

template<class D>

typedef RealVector::iterator etirm::ItemNR< D >::n_iterator

Type iterator over number of examinees who responded to an item.

Definition at line 66 of file ItemNR.h.

template<class D>

typedef D::point_iterator etirm::ItemNR< D >::point_iterator

Type iterator over quadrature points.

Definition at line 69 of file ItemNR.h.

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Constructor & Destructor Documentation

template<class D>

etirm::ItemNR< D >::ItemNR	(	int	nparam,
		int	index,
		int	respCat,
		D *	dist = 0
	)			[inline]

Constructor.

Template Parameters

Parameters:

D

Class for discrete latent variable distribution.

Function Parameters

Parameters:

[in]	nparam	Number of item parameters.
[in]	index	Zero-offset index of item in vector of all item responses.
[in]	respCat	Number of response categories.
[in]	dist	Latent variable distribution.

Definition at line 290 of file ItemNR.h.

References etirm::ItemNR< D >::mLatentDist, etirm::ItemNR< D >::mN, etirm::ItemNR< D >::mNumLatentVarCat, and etirm::ItemNR< D >::mR.

00290                                                                :
00291     Item<typename D::latentvar_type>(nparam, index, respCat),
00292 #else
00293         ItemNR<D>::ItemNR(int nparam, int index, int respCat, D *dist) : Item<D::latentvar_type>(nparam, index, respCat),
00294 #endif
00295         mLatentDist(dist), mR(0), mN(0), mNumLatentVarCat(0)
00296   {
00297     if (dist)
00298     {
00299       mNumLatentVarCat = dist->size();
00300       // Compute total number of latent distribution points over all groups for
00301       // which the points are unique
00302       int totpoints = mLatentDist->NumGroupsUnique() * mNumLatentVarCat;
00303 
00304       mR = new RealMatrix(respCat, totpoints);
00305       mN = new RealVector(totpoints);
00306     }
  }

template<class D>

etirm::ItemNR< D >::~ItemNR

(

)

[inline, virtual]

Destructor.

Definition at line 312 of file ItemNR.h.

References etirm::ItemNR< D >::mN, and etirm::ItemNR< D >::mR.

  {
    if (mN)
      delete mN;
    if (mR)
      delete mR;

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Member Function Documentation

template<class D>

ItemNR< D >::r_iterator etirm::ItemNR< D >::RVector	(	Response	resp,
		int	group = 1
	)			[inline]

Returns iterator to first element of row of mR corresponding to response "resp" for examinee group "group" (where the first examinee group is group 1).

Function Parameters

Parameters:

[in]	resp	Response vector.
[in]	group	Examinee group (default =1).

Definition at line 342 of file ItemNR.h.

References etirm::ItemNR< D >::mLatentDist, etirm::ItemNR< D >::mNumLatentVarCat, and etirm::ItemNR< D >::mR.

  {
    int ngroups = mLatentDist->NumGroups();
    if (group > ngroups || group < 1)
      throw InvalidArgument("Invalid group", "ItemNR::RVector");

    r_iterator rvec = mR->begin_row(Item<typename D::latentvar_type>::ResponseIndex(resp)+1); // Added "Item<typename D::latentvar_type>::" to ResponseIndex method call. ww, 1/12/2008

    return (mLatentDist->NumGroupsUnique() == 1) ? rvec : (rvec + (group-1) * mNumLatentVarCat);

template<class D>

ItemNR< D >::n_iterator etirm::ItemNR< D >::NVector

(

int

group = 1

)

[inline]

Returns iterator to first element of mN for examinee group "group" (where the first examinee group is group 1).

Function Parameters

Parameters:

[in]

group

Group index.

Definition at line 362 of file ItemNR.h.

References etirm::ItemNR< D >::mLatentDist, etirm::ItemNR< D >::mN, and etirm::ItemNR< D >::mNumLatentVarCat.

  {
    int ngroups = mLatentDist->NumGroups();
    if (group > ngroups || group < 1)
      throw InvalidArgument("Invalid group", "ItemNR::NVector");

    n_iterator nvec = mN->begin();
    return (mLatentDist->NumGroupsUnique() == 1) ? nvec : (nvec + (group-1) * mNumLatentVarCat);

template<class D>

void etirm::ItemNR< D >::SetLatentVarPoints	(	int	n,
		point_iterator	points
	)

Assigns values associated with discrete latent variable categories.

Note: I was not able to locate any SetLatentVarPoints function in the code base. It is questionable whether this function is operative at all (ww, 2-28-2008).

Function Parameters

Parameters:

[in]	n	Number of discrete categories of the latent ability distribution.
[in]	points	Iterator over quadrature points.

template<class D>

point_iterator etirm::ItemNR< D >::GetLatentVarPoints

(

int

group = 1

)

[inline]

Returns iterator over quadrature points.

Function Parameters

Parameters:

[in]

group

\ Examinee group (1, 2, ..., "number of groups").

Definition at line 137 of file ItemNR.h.

    {
      return mLatentDist->begin_points(group);
    }

template<class D>

int etirm::ItemNR< D >::NumLatentVarCat

(

)

[inline]

Returns number of discrete latent variable categories.

Definition at line 143 of file ItemNR.h.

    {
      return mNumLatentVarCat;
    }

template<class D>

void etirm::ItemNR< D >::InitializeNR

(

)

[inline]

Initializes elements of mR and mN to zero.

Definition at line 324 of file ItemNR.h.

References etirm::ItemNR< D >::mN, and etirm::ItemNR< D >::mR.

  {
    if (mN)
      *mN = 0.0;
    if (mR)
      *mR = 0.0;

template<class D>

virtual double etirm::ItemNR< D >::f_to_minimize

(

RealVector &

p

)

[pure virtual]

Function to maximize in M-step.

Function Parameters

Parameters:

[in]

&p

Address of item parameter vector.

Note: Technically, negative value of function is being minimized, so the negative function value is being returned.

Implemented in etirm::ItemDichotomous< D, ICC >, and etirm::ItemPolytomous< LC, M >.

template<class D>

virtual void etirm::ItemNR< D >::gradient	(	RealVector &	p,
		RealVector &	g
	)			[pure virtual]

Computes gradient of function to maximize in M-step.

Function Parameters

Parameters:

[in]	&p	Address of item parameter vector.
[out]	&g	Address of gradient vector. Gradient values are returned in the vector elements.

Note: Technically, negative value of function is being minimized, so the negative gradient is being returned.

Implemented in etirm::ItemDichotomous< D, ICC >, and etirm::ItemPolytomous< LC, M >.

template<class D>

virtual void etirm::ItemNR< D >::hessian	(	RealVector &	x,
		RealMatrix &	h
	)			[pure virtual]

Computes hessian of function to maximize in M-step.

Note: Technically, the negative value of the function is to be minimized by UNCMIN++, see inline comments in function code.

Note: The hessian is stored in the lower trangle of h.

Implemented in etirm::ItemDichotomous< D, ICC >, and etirm::ItemPolytomous< LC, M >.

template<class D>

virtual int etirm::ItemNR< D >::HasAnalyticGradient

(

)

const [pure virtual]

Function to indicate that the algebraic gradient of the item (ICCDeriv1) is defined.

This function can be used by UNCMIN++.

Implemented in etirm::ItemDichotomous< D, ICC >, and etirm::ItemPolytomous< LC, M >.

template<class D>

virtual int etirm::ItemNR< D >::HasAnalyticHessian

(

)

const [pure virtual]

Function to indicate that the algebraic hessian of the item (ICCDeriv2) is defined.

This function can be used by UNCMIN++.

Implemented in etirm::ItemDichotomous< D, ICC >, and etirm::ItemPolytomous< LC, M >.

template<class D>

int etirm::ItemNR< D >::ValidParameters	(	const RealVector &	p,
		bool	ignorePriors = false
	)			const [inline, virtual]

Returns 1 if all parameters have a non-zero prior density, or 0 otherwise.

Function Parameters

Parameters:

[in]	&p	Address of parameter vector for this item.
[in]	ignorePriors	Boolan flag to bypass the test of prior densities.

Reimplemented in etirm::ItemDichotomous< D, ICC >.

Definition at line 381 of file ItemNR.h.

  {
    // For each parameter check that prior density at the value of the
    // parameter is not zero
    if (!ignorePriors)
    {
      PriorVector::const_iterator iprior = Item<typename D::latentvar_type>::mPriors.begin();
      RealVector::const_iterator iparam = param.begin();
      for (int i=Item<typename D::latentvar_type>::NumParameters(); i--; ++iprior, ++iparam) // Added "Item<typename D::latentvar_type>::" to NumParameters method call. ww, 1/12/2008
      {
        if (*iprior)
        {
          if ((*iprior)->ZeroDensity(*iparam))
          {
            return 0;
          }
        }
      }
    }
    return 1;

template<class D>

int etirm::ItemNR< D >::dim

(

)

const [inline]

Number of item parameters.

Definition at line 226 of file ItemNR.h.

    {
      return Item<typename D::latentvar_type>::NumParameters();
    } // Added "Item<typename D::latentvar_type>::" to NumParameters method call. ww, 1/12/2008

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Member Data Documentation

template<class D>

D* etirm::ItemNR< D >::mLatentDist [protected]

Latent variable distribution used to determine discrete categories on the latent variable.

Definition at line 234 of file ItemNR.h.

Referenced by etirm::ItemNR< LC >::GetLatentVarPoints(), etirm::ItemNR< D >::ItemNR(), etirm::ItemNR< D >::NVector(), and etirm::ItemNR< D >::RVector().

template<class D>

RealMatrix* etirm::ItemNR< D >::mR [protected]

Expected number of respondents in each latent variable category who took this item and gave the i-th response.

If there are different points for different examinee groups the expected number of examinees will differ for different groups, and will be stacked in each row.

The first mNumLatentVarCat values will be for the first group, the second mNumLatentVarCat values will be for the second group, etc. These expected counts are computed in the E-step.

Definition at line 249 of file ItemNR.h.

Referenced by etirm::ItemNR< D >::InitializeNR(), etirm::ItemNR< D >::ItemNR(), etirm::ItemNR< D >::RVector(), and etirm::ItemNR< D >::~ItemNR().

template<class D>

RealVector* etirm::ItemNR< D >::mN [protected]

Expected number of examinees who took this item in each latent variable category.

If there are different points for different examinee groups the expected number of examinees will differ for different groups, and will be stacked.

The first mNumLatentVarCat values will be for the first group, the second mNumLatentVarCat values will be for the second group, etc. These expected counts are computed in the E-step.

Definition at line 264 of file ItemNR.h.

Referenced by etirm::ItemNR< D >::InitializeNR(), etirm::ItemNR< D >::ItemNR(), etirm::ItemNR< D >::NVector(), and etirm::ItemNR< D >::~ItemNR().

template<class D>

int etirm::ItemNR< D >::mNumLatentVarCat [protected]

Number of latent variable categories.

Definition at line 268 of file ItemNR.h.

Referenced by etirm::ItemNR< D >::ItemNR(), etirm::ItemNR< LC >::NumLatentVarCat(), etirm::ItemNR< D >::NVector(), and etirm::ItemNR< D >::RVector().

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The documentation for this class was generated from the following file:

• C:/programs/etirm/src/ItemNR.h

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