Change in item parameters across unidimensional and multidimensioanl models

[Georg II]

I have analysed the same test once with a unidimensional model and once with a multidimensional model using ConQuest. In the two dimensional model the items are assigned to two dimensions. The two-dimensional model fits significantly better. However, item difficulty parameters are very different in the two models. What does this mean?
I remember I read somewhere that when item parameters across the two models are very different, it means that the better fitting model has done a better job of accounting for the data and was necessary for modeling the data. Is that right? I can’t locate the reference now. Would be thankful if you directed me to the appropriate source.

Regards
Georg II

[Eveline Gebhardt]

Hi Georg II

Is each item only assigned to one of the two dimensions, or do they load on both?

If each item is assigned to only one dimension, you could have a look at a scatter plot between the item parameters of the two models. I expect you'll see two lines, one for each dimension. The default in ConQuest is to constrain items, which means that the average item difficulty is set to zero for each dimension. Hence there is a shift in item difficulties for each dimension.

Eveline