[Xcalibre 4.1]-Pure logistic model vs Logistic approximation

I have started using the brand new Xcalibre 4.1 software for Item Response theory and there are a number of elements I am unfamiliar with. The program requires me to state if I am using a pure logistic model or a logistic approximation. I have created a measure of 29 questions and each item is on a scale of 0-6. I understand a logistic approximation is an approximation of the normal curve, but I do not know what a pure logistic model is or which I should be using

Can anyone tell me which is right for me? Much appreciated!
No, it says Model Constant: D=1.0 (pure logistic model)
D=1.7 (logistic approximation)

And I am supposed to choose one or the other. Thanks for the reply!


Can't make spagetti
Masteras is exactly right... an intercept of 1.7 is the psychometric improvement of the more widely used pi/sqrt(3) approximation of a probit mode which minimises the discrepancy between the logistic and the normal distributions... whether you choose a logistic over a probit model (or vice-versa) is always subject to debate in the psychometric literature... none is better than the other one, it depends on the assumptions behind what you're trying to model...


Can't make spagetti
hey, it was all you who pointed out the correct difference, i just placed it on a psychometric framework which i guess could help expand a little bit on the answer... ;)