extract {GDINA}

extract elements from objects of various classes

Description

A generic function to extract elements from objects of class GDINA, itemfit, modelcomp, Qval or simGDINA. This page gives the elements that can be extracted from the class GDINA. To see what can be extracted from itemfit, modelcomp, and Qval, go to the corresponding function help page.

Objects which can be extracted from GDINA objects include:

AIC

AIC

att.prior

attribute prior weights for calculating marginalized likelihood in the last EM iteration

attributepattern

all attribute patterns involved in the current calibration

BIC

BIC

CAIC

Consistent AIC

catprob.cov

covariance matrix of item probability parameter estimates; Need to specify SE.type

catprob.parm

item parameter estimates

catprob.se

standard error of item probability parameter estimates; Need to specify SE.type

convergence

TRUE if the calibration is converged.

dat

raw data

del.ind

deleted observation number

delta.cov

covariance matrix of delta parameter estimates; Need to specify SE.type

delta.parm

delta parameter estimates

delta.se

standard error of delta parameter estimates; Need to specify SE.type

designmatrix

A list of design matrices for each item/category

deviance

deviance, or negative two times observed marginal log likelihood

discrim

GDINA discrimination index

expectedCorrect

expected # of examinees in each latent group answering item correctly

expectedTotal

expected # of examinees in each latent group

higher.order

higher-order model specifications

LCprob.parm

success probabilities for all latent classes

logLik

observed marginal log likelihood

linkfunc

link functions for each item

initial.catprob

initial item category probability parameters

natt

number of attributes

ncat

number of categories

ngroup

number of groups

nitem

number of items

nitr

number of EM iterations

nobs

number of observations, or sample size

nLC

number of latent classes

prevalence

prevalence of each attribute

posterior.prob

posterior weights for each latent class

reduced.LG

Reduced latent group for each item

SABIC

Sample size Adusted BIC

sequential

is a sequential model fitted?

Usage

extract(object, what, ...)

Arguments

object

objects from class GDINA,itemfit, modelcomp, Qval or simGDINA

what

what to extract

...

additional arguments

Examples

## Not run: 
dat <- sim10GDINA$simdat
Q <- sim10GDINA$simQ
fit <- GDINA(dat = dat, Q = Q, model = "GDINA")
extract(fit,"discrim")
extract(fit,"designmatrix")

## End(Not run)