My data is 2688 by 200, with 0/1 coded. I am trying to estimate both parameters and ability(theta) using 2PL logistic model.
First I use the following code to get parameter estimate:
fit2PL = ltm(dat ~ z1, IRT.param = TRUE)
Then use the following to get theta estimate
theta<-ltm::factor.scores(fit2PL)
Now I want to extract zl column (i.e., theta estimate) from theta, the following code is not working. please help
theta1<-theta$zl
thank you!
Hi, and welcome!
A minimum working example, called a reprex will attract more and better answers.
library(ltm)
#> Loading required package: MASS
#> Loading required package: msm
#> Loading required package: polycor
# example from help(factor.scores)
fit <- rasch(LSAT)
f_scores <- factor.scores(fit) # Empirical Bayes
# f_scores is NOT a data frame
class(f_scores)
#> [1] "fscores"
# show the structure
str(f_scores)
#> List of 6
#> $ score.dat:'data.frame': 30 obs. of 9 variables:
#> ..$ Item 1: num [1:30] 0 0 0 0 0 0 0 0 0 0 ...
#> ..$ Item 2: num [1:30] 0 0 0 0 0 0 0 0 1 1 ...
#> ..$ Item 3: num [1:30] 0 0 0 0 1 1 1 1 0 0 ...
#> ..$ Item 4: num [1:30] 0 0 1 1 0 0 1 1 0 0 ...
#> ..$ Item 5: num [1:30] 0 1 0 1 0 1 0 1 0 1 ...
#> ..$ Obs : num [1:30] 3 6 2 11 1 1 3 4 1 8 ...
#> ..$ Exp : num [1:30] 2.364 5.468 2.474 8.249 0.852 ...
#> ..$ z1 : num [1:30] -1.91 -1.439 -1.439 -0.959 -1.439 ...
#> ..$ se.z1 : num [1:30] 0.79 0.793 0.793 0.801 0.793 ...
#> $ method : chr "EB"
#> $ B : num 5
#> $ call : language rasch(data = LSAT)
#> $ resp.pats: logi FALSE
#> $ coef : num [1:5, 1:2] -3.615 -1.322 -0.318 -1.73 -2.78 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:5] "Item 1" "Item 2" "Item 3" "Item 4" ...
#> .. ..$ : chr [1:2] "Dffclt" "Dscrmn"
#> - attr(*, "class")= chr "fscores"
# now we know how to call z1
f_scores$score.dat$z1
#> [1] -1.91035438 -1.43850427 -1.43850427 -0.95942992 -1.43850427 -0.95942992
#> [7] -0.95942992 -0.46601739 -1.43850427 -0.95942992 -0.46601739 -0.46601739
#> [13] -0.46601739 0.04900961 -1.43850427 -0.95942992 -0.95942992 -0.46601739
#> [19] -0.95942992 -0.46601739 -0.46601739 0.04900960 -0.95942992 -0.46601739
#> [25] -0.46601739 0.04900961 -0.46601739 0.04900960 0.04900961 0.59301137
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