[R] ability estimate with GRM of IRT

[Dimitris Rizopoulos]

you need to use the 'resp.patterns' argument of factor.scores(); look 
at ?factor.scores for more info, e.g.,

library(ltm)

fit <- grm(Environment)
factor.scores(fit)
factor.scores(fit, resp.patterns = Environment)


I hope it helps.

Best,
Dimitris

ps, it'd be better not to call your fitted GRM model 'grm'; check

library(fortunes)
fortune("dog")

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "SHEN,FENG" <fshen at ufl.edu>
To: <r-help at stat.math.ethz.ch>
Sent: Friday, January 19, 2007 5:30 AM
Subject: [R] ability estimate with GRM of IRT


> Hi my friends,
>
> I have an issue with ability estimates when running GRM of IRT.  I
> have responses from 242 subjects but got 183 ability estimates.
> Below is what I did to get the estimates.
>
> 1) I have a csv file "P1.csv" and I imported it into R and loaded
> the "ltm" package by doing:
> p1<-read.table("P1.csv",header=TRUE,sep=",")
> library(ltm)
>
> 2) I created a subset that included columns 2 to 9 for the
> analysis by doing:
> s1<-p1[,2:9]
>
> 3) I converted the subset into data.frame format by doing:
> s1df=data.frame(s1)
>
> 4) I checked the descriptive stats for the s1df by doing:
> ds1df=descript(s1df)
> ds1df
>
> And it was confirmed that 242 subjects' responses were imported.
>
> 5)I ran GRM on the s1df dataset by doing:
> grm<-grm(s1df, Hessian=T)
> grm
>
> 6)Finally, I ran the ability estimated by doing:
> aes1=factor.scores(grm)
> aes1
>
> And I got 183 factor-scores for observed response patterns.
> Besides, the 183 estimates are not for the first 183 subjects of
> the 242 because the response patterns of No 1 on the factor-scores
> list do not match those of No 1 in the s1 dataset and the same
> thing holds true for the rest of the response patterns.
>
> Could you help me find out what the problem is?
>
> Many thanks in advance!
>
> Feng
>
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