search for: missingwa

...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...