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Hi, I analyzed a data using CFA with Mplus and then analyzed it using Rasch model(1PL) with WINSTEPS. However, I heard that CFA in Mplus is similar to a two parameter IRT model. So, did I make a mistake? Thank you in advance. 


If you want a Rasch model in Mplus, you should hold the factor loadings equal and set the metric of the factor by fixing the factor variance to one. 


Hi, I'm doing a 3dimensional Rasch analysis with MPlus, please can you give me a hint for this question: How do I get any reliability indicators such as PSI (person separation index, cf. RUMM2030 software) oder EAP/ PV (cf. Conquest software)? Thank you very much in advance, Andreas 


Those statistics are not given in Mplus. 


Thank you for your answer! How is item fit (according to the Rasch model) evaluated in MPlus? I found standardized residuals that might indicate significant misfit when they exceed +/ 1,96. Is that correct? Are there other fit statistics concerning the Rasch model in MPlus? Thank you, Andreas 


The TECH10 residuals you are looking at are the best way to assess model fit with categorical items and maximum likelihood estimation. There are no absolute fit statistics. 

tomlife posted on Wednesday, March 25, 2015  8:49 am



I have a similar problem. I analyzed Data using (nine dimensional) ordinal Rasch model in ConQuest. Due to the fact that Conquest doesn't compute standard errors or confidence intervall, which are necessary to compare the latent correlations betwenn the dimensions, I tried to reproduce the model in Mplus. So I set all factors (for each dimension) equal and the variance (for each dimension) @ 1, estimation via MLR. For 16 of 18 relevant correlations the results by Mplus are nearly the same as by ConQuest (+/ .02), but for the other two correlations there are greater differences (> .1) which also change the result pattern. Do yor have any ideas, what causes these differences? 


You want to compare the loglikelihood values that the 2 programs give to see if they have found the same solution. Although, I don't know if ConQuest uses ML (MLR) or some other estimator. With 9 dimensions using ML(R) there is also the issue of precision in the numerical integration. Are you using integration=montecarlo(5000)? 

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