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From |
"Verkuilen, Jay" <JVerkuilen@gc.cuny.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: IRT with GLLAMM |

Date |
Mon, 16 Mar 2009 14:42:52 -0400 |

Jean-Benoit Hardouin wrote: >There is two a frequentist appoach which is the ONE Parameter Logistic Model (OPLM) which is different of the 1-PLM(=Rasch model). The OPLM allows defining a value of slope (discriminating power) different for each item. The difference with the 2PLM is that this slopes are a priori fixed by the user. The properties of the OPLM are very close of the Rasch model (objective measure, exhaustivity of the score), with a besser flexibility compare to the Rasch model. This is possible to implement this model with gllamm> Hmmm, so you fix the slope a priori. I'm not familiar with this model as a "named" model but it begs the question of how you got the slope first. >> Just to note this is an area of substantial dispute. >Yes !! The "heat" of the dispute seems to be dying down, finally. >I don't hate the 2PLM but I don't see any advantage of this model compared to the Rasch family model (which have nice measurement properties) or compared to the Classical Test Theory (where the measure generally is more reliable). I think the 2PLM is a pretty statistical tool to verify the proposition "the model should have a good fit to the data", but is not a very usefull model for a practical use (in the idea to create a measure with good properties (psychometric point of view) or reliable (practical point of view)).> Whereas I think classical test theory is a crummy approximation to the analysis you really wanted to do in the first place. I suspect much depends on one's training---mine was from Rod McDonald, and thus I view IRT as simply a special factor analysis for binary items that deals with the nonlinear regression between latent trait and observed responses. Unidimensional IRT isn't something particularly desirable. >>If the Rasch model don't agree with another population than this one used to check the fit, then there is Differential Item Functionning which is well described in the literatture and which can be taking account, even with the Rasch model !<< Hmmm, DIF is not how I'd think about that problem. My issue was to consider a set of data someone gave you. You want to analyze it, let's say to screen for "good" items you plan on testing again sometime later. In this case a 2PL type model (or even other things like a nonparametric model) will be helpful. This is best done with a good set of items to anchor things, though. So if you have a set of items you understand, perhaps built according to the Rasch model, it makes sense to use a 2PL (or restricted 2PL, or some other) to analyze them to see if the new items perform similar to the old items. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: IRT with GLLAMM***From:*Jean-Benoit Hardouin <jean-benoit.hardouin@neuf.fr>

**RE: st: IRT with GLLAMM***From:*"Verkuilen, Jay" <JVerkuilen@gc.cuny.edu>

**Re: st: IRT with GLLAMM***From:*Jean-Benoit Hardouin <jean-benoit.hardouin@univ-nantes.fr>

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