Dear All,
I am Ph.D student at Chulalongkorn University in Thailand, I want to use
Package 'sampleSection' to estimate missing data which generate under IRT
model(3-PL);
n<-500 ## number of examinee
I<-20 ## number of items
num.imp<-5 ##number of imputations
p.missing<-c(0.09, 0.01) #prob of missing
theta<-sort(rnorm(n,0,1)) #ability
a<-rnorm(I,0.5,0.1) #discrimination
b<-rnorm(I,0,1) #difficulty
c<-runif(I,0,0.25) #guess
Only item 1 have missing data. If the response to items 1 was a 1 (correct),
the probability of missingwas 1%. If the
response was a 0 (incorrect), the probability of missing was 9%. Thus, the
probability of missing was linked to the response of items itself (an unknown
characteristic in real missing data situations).
I don't know how to apply function 'Heckman-style selection models' for this
case, becase all my variables are unobserved.
Could you please tell me how to estimate data under my situation.
I'am looking forward your advice.
Sincerely yours,
Kamontip Srihaset
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
