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can item fit statistics fit the rasch model while having disordered probability curves?

god bless the existence of this video and availablility to watch

I am always respecting you!!

Hai Prof Michael. I'm curious about rasch regression analysis. Can you help me to understand this analysis?

Thank you for this valuable opportunity to see one o Rasch modeling pioneers in action.

This is a great lecture, Dr. Linacre. Would you upload your lectures on Marginal Maximum Likelihood Estimation as well, if you have any recordings of those?

brilliant Mike. Thank you.

You are the best of the best!! I learned so much!!

This is incredibly helpful! Thank you for sharing!

It's a pleasure to understand how Rasch Measurement works from one of the giants of the field himself! Thank you Dr. Linacre for sharing this lecture!

Lovely! Finally, I got to understand it!!

Great explanation really, i wish the whole lecture is uploaded. Thanks a lot for the great video.

Thank you very much for this tutorial. I've watched it a number of times. When I re-watch (to analyse a different set of data), I gained a better understanding.

Thank you, Dr. Linacre. This video is very helpful.

Dr Linacre, i tried to import in an excel file but got an error,; WININPUT 4.6.0 at excelmod line: 22070 Error: 1AD ActiveX component can't create object. Could i check why is this so? I ensure there is only 1 tab in the excel file

Thank you professor. btw, you made me think of my grandpa.

The video is not clearer... I can't read what he wrote in the board/ pointed in the flip-chart. However, his explanation was very understandable!

Hi Mike, this was a great video, thank. My version of WINSTEPS is 3.68.2, is it not possible to do several of these steps in this version? For example, there is no Table 23.1. Thanks in advance, Kim

You rock! Best video ever! Super helpful for my Master's!

Thank you!

thank youuuu

Thank you for this!

Yes, me too! So helpful. Thank uuuu

In table 23.2, the red box looks like the Knox Cube data while the blue box looks like the Liking for Science. Did you purposely combine the two sets of data to show there are 2 dimensions?

so cute lol, helpful too (:

Professor Linacre, thank you for your video, very useful to help me in my research projects and easily explained to quickly understand new concepts!

This is very helpful, thank you. g

You are amazing! Thank you so much, this video is very helpful!

Thanks fort sharing thi

Can we do this in FACETS as well?

Hello and thank you for the helpful video. When I run Rasch analysis I do not get the correlation table (with pearson and dissattenuated correlation values) following table 1. Can you please suggest how to reproduce those outputs. Also how can i reporduce the excel graph. I went through the manual and I do not find the suggested on my winsteps screen option through output tables or plots ? Please guide

Thank you Dr. Linacre. This is of great help and great update on analyzing dimensionality

John - very useful. To clear up a confusion: person measures from items of Cluster 1 versus person measures from items of Cluster 3 correlated at -.17, and in the simulated the same correlation was .2, that's quite difficult to compare! so do we conclude that the -.17 was expected given the data since it's nearer zero, or do we conclude that -.17 was so far from the .2 that the -.17 was not expected given the data. If we're simulating according to a unidimensional Rasch model would we expect all person measures from item clusters to be positively correlated? To me the negative correlation is enough to conclude weirdness without checking against the equivalent correlation from simulated data. e.g. parallel analysis would compare eigenvalues against those expected given simulated data, but eigenvalues can't go negative.

cool I go it

Dr. Linacre, Where could I find one of these tables that you use in this lecture?

Thank you Dr. Linacre for uploading these videos. They are of real help.

Thank you very much for sharing this!

Nice interview. I think that the confusion in research still continues.

Dr. Linacre, I also noticed on sample datasets that the estimated Rasch discrimination problems when I request, discrim = yes, corresponds almost perfectly with Infit problems. Would this be a case that Infit/Outfit can be an index of problems with discrimination?

Thank you also for posting the other videos with Ben Wright. No matter how many books I read, his explanations are so clear that it is a great resource in addition to what we read about.

Very nice presentation. I would assume that it would be difficult to show JMLE (the unconditional) in action. Dr. Linacre, is there a real improvement in terms of the Marginal Maximum likelihood worked out by Darrell Bock that IRT programs use?; when I ran simulations the differences were really negligible. Peter Paprzycki

Dr. Linacre, I am a Data Analytics undergraduate student and researcher at Ohio State, and am applying the Rasch model to survey data I have on childhood stressors. This helped me to understand the model so much better. Thank you very much! Elizabeth Gilbert

Thanks for posting this, Prof.

Thanks to your effort, wise science and practical reason will prevail in the the fields of Psychometrics and Measurement!. Historical video.

Dear professor, your job is an inspiration. Thanks for Facets and for all your support.

Excellent!

Very nice and clear.

Very nice video.

I had the fortune of meeting and discussing with yourself as well as with Ben in the early 2000's and this made an incredible impact on my scientific thinking, career and anything related to all of that. I remember walking out from Judd Hall feeling like a new (much more sense making) word had been revealed to me! So, thank you so much for sharing this, Mike. It is tremendously important - of course regarding the specifics of Rasch measurement but even more so regarding Ben's (and others) thoughts on science in general. Particularly, I love the sequence when he says "There is never data that is complete. The idea that you have complete data is an illusion. The people who ask 20 questions and happen to get 20 answers think they got, but if they realize that the 20 answers they got are just a sample of the 20 questions they might have asked, there is already missing data to all the questions they might have asked. And as a matter of fact, from examining data more carefully from the programs you have written [i.e. Mike] we can show that in many cases a person that answers a question in many cases might as well be missing data because if that question didn't function the same way that the others did….. so these are ”invisible” missing data… So, THE PHILOSOPHY OF INFERENCE REQUIRES YOU TO BE ABLE TO SAY SOMETHING ABOUT THE FUTURE BASED ON THE INCOMPLETE INFORMATION YOU HAVE FROM THE PAST”. This is just SOOOO propound - regardless of which åarticular "Rasch school" you may happen to attach yourself to. So - thanks. And I hope you will post whatever additional video materials you may have access to on this youtube channel - so much appreciated!

Dear John, thank you. Can you upload more videos regarding Rasch measurement.