m4plModelShow {irtProb} | R Documentation |
Show all the information about the estimation of all the possible m4pl models for each subjects.
m4plModelShow(x, ...)
x |
data.frame: a matrix of binary 0-1 item responses. |
... |
varying: parameters to be passed to the
m4plPersonParameters function. |
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 |
Gilles Raiche, Universite du Quebec a Montreal (UQAM),
Departement d'education et pedagogie
Raiche.Gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/
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/
## 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