Re: Multidimensional EFA - reverse scoring or not

[Phil Chalmers]

Yes, this sounds correct to me. For MIRT models reverse scoring is not really important except in special cases (e.g., non-compensatory models), and is largely done for convenience. Note that the next version of the package will include a reverse.score() function anyway as this is common practice still, and is still useful in some contexts (like computing EAP tables for sum scores). 

Phil

On Wed, Jul 12, 2023 at 2:55 AM zha...@gmail.com <zhao...@gmail.com> wrote:

Hi all,

In uni-dimensional Rasch models, we normally reverse score some items so that all items are in the same direction of the latent variable/trait.

I am wondering if we need to do the same for a multi-dimensional IRT model? 

For EFA, as we don't know what the underlying factors are, I think reverse scoring sounds irrelevant here.

On the other hand, even with CFA, if we allow items to be loaded to different factors (compensatory), those items could be positively loaded to one factor and negatively loaded to another factor. So, I am guessing the reverse scoring is also not applicable here.

Is my understanding correct? 

Thanks in advance.

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