Mixture IRT model in the mirt package

[Farshad Effatpanah]

Dear Phil and all,

I hope you are doing well. I am applying mixture IRT models to the reading comprehension section  of a high-stakes multiple-choice test using the mirt package. I have faced two issues that I would be grateful if you could assist.

1- Item difficulties are in logit (IRTpars=TRUE to coef()). Is discrimination also in logit? Is in the 2PL, as implemented in mirt, the logit scale is used? I am not sure whether a different link function is used or not.

2- In addition, the TAM package uses the equal-mean-difficulty anchor method for DIF analysis. This method assumes that the mean of difficulty across items is the same
across classes or (sub)groups (typically equal to zero). In fact, the mean of difficulty parameters across items was constrained to be equal to zero for each latent class

in mixed Rasch model analysis. How about the mirt package? In my results, there are two latent classes. The mean of item difficulties for Class 1 is 1.207, and for Class 2 is 0.8295.

The examination of person parameters based on the WLE estimates show that the mean of person parameters for Class 1 is -0.004, and for Class 2 is 0.012. 

How can I set the mean of item difficulties to zero, but allow person parameters vary?

I would be grateful if you could help.

Best,

Farshad