m4plModelShow: Results For Each Subject To Each Model

Description Usage Arguments Value Author(s) References See Also Examples

Description

Show all the information about the estimation of all the possible m4pl models for each subjects.

Usage

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Arguments

x

data.frame: a matrix of binary 0-1 item responses.

...

varying: parameters to be passed to the m4plPersonParameters function.

Value

ID

integer: subject identificator.

MODEL

charavter: model identification (T,TS,TC,TD,TSC,TSD,TCD or TSCD)

LL

numeric: loglikelihood.

AIC

numeric: Akaike information criteria.

BIC

numeric: Bayes (Schwartz) information criteria.

T

numeric: theta parameter value.

SeT

numeric: theta parameter theoretical standard error.

S

numeric: person fluctuation parameter value.

SeS

numeric: person fluctuation theoretical standard error

C

numeric: person pseudo-guessing parameter value.

SeC

numeric: person pseudo-guessing theoretical standard error

D

numeric: person inattention parameter value.

SeD

numeric: person inattention theoretical standard error

Author(s)

Gilles Raiche, Universite du Quebec a Montreal (UQAM),

Departement d'education et pedagogie

Raiche.Gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/

References

Blais, J.-G., Raiche, G. and Magis, D. (2009). La detection des patrons de reponses problematiques dans le contexte des tests informatises. In Blais, J.-G. (Ed.): Evaluation des apprentissages et technologies de l'information et de la communication : enjeux, applications et modeles de mesure. Ste-Foy, Quebec: Presses de l'Universite Laval.

Raiche, G., Magis, D. and Beland, S. (2009). La correction du resultat d'un etudiant en presence de tentatives de fraudes. Communication presentee a l'Universite du Quebec a Montreal. Retrieved from http://www.camri.uqam.ca/camri/camriBase/

Raiche, G., Magis, D. and Blais, J.-G. (2008). Multidimensional item response theory models integrating additional inattention, pseudo-guessing, and discrimination person parameters. Communication at the annual international Psychometric Society meeting, Durham, New Hamshire. Retrieved from http://www.camri.uqam.ca/camri/camriBase/

Raiche, G., Magis, D., Blais, J.-G., and Brochu, P. (2013). Taking atypical response patterns into account: a multidimensional measurement model from item response theory. In M. Simon, K. Ercikan, and M. Rousseau (Eds), Improving large-scale assessment in education. New York, New York: Routledge.

See Also

m4plPersonParameters

Examples

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## Not run: 
## GENERATION OF VECTORS OF RESPONSES
 # NOTE THE USUAL PARAMETRIZATION OF THE ITEM DISCRIMINATION,
 # THE VALUE OF THE PERSONNAL FLUCTUATION FIXED AT 0,
 # AND THE VALUE OF THE PERSONNAL PSEUDO-GUESSING FIXED AT 0.30.
 # IT COULD BE TYPICAL OF PLAGIARISM BEHAVIOR.
 nItems <- 40
 a      <- rep(1.702,nItems); b <- seq(-5,5,length=nItems)
 c      <- rep(0,nItems); d <- rep(1,nItems)
 nSubjects <- 1; rep <- 100
 theta     <- seq(-1,-1,length=nSubjects)
 S         <- runif(n=nSubjects,min=0.0,max=0.0)
 C         <- runif(n=nSubjects,min=0.3,max=0.3)
 D         <- runif(n=nSubjects,min=0.0,max=0.0)
 set.seed(seed = 100)
 X         <- ggrm4pl(n=nItems, rep=rep,
                      theta=theta, S=S, C=C, D=D,
                      s=1/a, b=b,c=c,d=d)

## Results for each subjects for each models
 essai <- m4plModelShow(X, b=b, s=1/a, c=c, d=d, m=0, prior="uniform")
 
## Mean results for some speficic models
 median(essai[which(essai$MODEL == "TSCD") ,]$SeT, na.rm=TRUE)
 mean(  essai[which(essai$MODEL == "TSCD") ,]$SeT, na.rm=TRUE)
 mean(  essai[which(essai$MODEL ==   "TD") ,]$SeT, na.rm=TRUE)
 sd(    essai[which(essai$MODEL ==   "TD") ,]$T, na.rm=TRUE)
 
## Result for each models for the first subject
 essai[which(essai$ID == 1) ,]
 max(essai[which(essai$ID == 1) ,]$LL)

## Difference between the estimated values with the T and TSCD models for the
## first subject
 essai[which(essai$ID == 1 & essai$MODEL == "T"),]$T
       - essai[which(essai$ID == 1 & essai$MODEL == "TSCD"),]$T

## End(Not run)

irtProb documentation built on May 2, 2019, 1:30 p.m.