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 wayne smith posted on Monday, May 09, 2016 - 2:25 am
Hello,

I am attempting a BSEM for categorical data with crossloadings for the first time. How do I set priors for this data which is largely skewed?12 items ordinal 0-5 scoring(psych outcome complex items). A CFA fit well with two crossloading items. I attempted to put this in a Bifactor CFA but saw I should not have crossloaders in bifactor CFA so I would like to use BSEM. I followed your examples using '~ N(0.1, 0.01)' for priors but I'm not sure if this is appropriate here.

MODEL:
Gen BY I01-I12*; Gen@1;

f1 BY I01* I03 I06 I08;
f2 BY I02* I07 I08;
f3 BY I04* I05 I10;
f4 BY I09* I10 I11 I12;

f1-f4@1;
Gen WITH f1-f4@0;
!crossloaders

f1 BY I02 I04 I05 I07 I09 I10 I11 I12*0 (ax1-ax8);

f2 BY I01 I03 I04 I05 I06 I09 I10 I11 I12*0(bx9-bx17);

f3 BY I01 I02 I03 I06 I07 I08 I09 I11 I12*0 (cx18-cx26);

f4 BY 01-I08*0 (dx27-dx34);

MODEL PRIORS:
ax1-dx34 ~N(0,0.01);

OUTPUT: TECH1 TECH8 STDY;
PLOT: TYPE = PLOT2;

Is the N(0,0.01) an OK choice here? Or considering item 8 and item 10 crossload 0.3 and 0.5 resp should I use an alternative?

Many thanks
 Bengt O. Muthen posted on Tuesday, May 10, 2016 - 6:49 pm
Yes, that prior is an ok choice. Large cross-loadings will show up as significant estimates and you can then free them if you want. But try some other variance values as well (smaller and larger) and see how it affects results.
 wayne smith posted on Wednesday, May 11, 2016 - 9:05 am
Thank you for your help.
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