According to Stan Manual (Version 2.18.1, page 33):

Non-centered parameterizations tend to be more efficient in hierarchical models;

However, I’m experimenting with a 3-PL IRT model, very similar to the one proposed by the manual (at the same page) and the centered version is much faster. Moreover, the estimation of the `beta`

parameter is more precise.

In this forest plot the red plots refer to the non-centered model, the blue ones to the centered model. Sampling was done with 4 chains, with 2000 draws.

I was surprised, since I expected the non-centered model were better. In fact, the centered model is easier to interpret (the estimated `beta`

is directly the value for a 50% success probability in the item response curve), thus it is definitely preferable.

I am not a stats experts, thus I wonder if there is something that I’m interpreting wrongly. Thanks in advance.