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WJCAO posted on Tuesday, September 20, 2011  7:16 am



Hi, I'm trying to use Montecarlo in Mplus to generate 40 categorical variables with 6 factors.Then MLR were used to analysis these data.But I got error: *** ERROR in MODEL command EFA factors are not allowed with ALGORITHM=INTEGRATION. EFA factors are declared with (*label). Montecarlo: names are y1y40; nobservations = 500; nreps = 500; seed = 12345; generate = y1y40(3 p); categorical = y1y40; Model population: f1 by y1y5* .4; f2 by y6y13* .5; f3 by y14y21* .6; f4 by y22y27* .7; f5 by y28y33* .8; f6 by y34y40* .9; y1y40* 1; f1f6*1; ANALYSIS: ESTIMATOR = MLR; Model: f1 by y1y5* .4 y6y40*0 (*1); f2 by y1y5*0 y6y13* .5 y13y40*0(*1); f3 by y1y13*0 y14y21* .6 y21y40*0(*1); f4 by y1y21*0 y22y27* .7 y28y40*0(*1); f5 by y1y27*0 y28y33* .8 y34y40*0(*1); f6 by y1y33*0 y34y40* .9(*1); y1y40* 1; f1f6*1; OUTPUT: TECH9; 


I think this can be done only with the WLSMV estimator. Try that. 

WJCAO posted on Tuesday, September 20, 2011  6:27 pm



Thank you.But I know we can use MLR with categorical outcomes for regular EFA or for CFA.And in this simmulation, the aim of our research is to recover the difference between MLR and WLSMV. So, under this scenario, what can I do? 


You would need to generate the data and save the data sets in one step and analyze each data set separately and put the results together yourself. Mplusautomation may be helpful. See the lefthand column fo the website for further information. 

WJCAO posted on Wednesday, September 21, 2011  8:18 am



Thank you. I have do as you said.But I cannot generate data sucessfully.And the EXAMPLE 11.5 in Mplus User's Guide cannot do too. The data I got is not a four category indicators. Montecarlo: names are y1y40; nobservations = 500; nreps = 1; seed = 12345; generate = y1y40(3 p); categorical = y1y40; save=M1.dat; Model population: f1 by y1y5* .4; f2 by y6y13* .5; f3 by y14y21* .6; f4 by y22y27* .7; f5 by y28y33* .8; f6 by y34y40* .9; y1y40* 1; f1f6@1; 


You need to give threshold population parameter values in MODEL POPULATION. See mcex7.6 where threecategory variables are generated. 

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