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 Paul Silvia posted on Wednesday, April 28, 2010 - 5:50 am
Hi:

Congrats on a rich and mature update. I was wondering what books you might recommend for those of us new to the Bayesian/MCMC approach to SEM estimation.

All the best,

Paul
 Bengt O. Muthen posted on Wednesday, April 28, 2010 - 7:28 am
Thanks from the whole Mplus team.

Funny you should ask about Bayes books - I have a about a dozen sitting on the floor. Many are good. Two stand out so far:

Gelman, Carlin, Stern & Rubin (2004). Bayesian data analysis. - My favorite among "advanced" texts.

Lynch (2010). Introduction to applied Bayesian statistics and estimation for social scientists. - A somewhat more applied book

Lots of good articles as well. I will reference some of them in my writing "A brief introdution to using Bayes in Mplus", which will be posted before too long.
 davide morselli posted on Monday, December 09, 2013 - 7:24 am
Hi,
I was wondering whether it makes sense to interpret p-values in BSEM the same way than in frequentist approach (rejection over a certain threshold).
Similarly, standardized coefficients in BSEM are interpreted in the same way than in ML?

thank you

Davide
 Linda K. Muthen posted on Monday, December 09, 2013 - 10:58 am
No, the p-values are not interpreted in the same way as in the frequentist approach. With Bayes, you should interpret the credibility intervals.
 davide morselli posted on Monday, December 09, 2013 - 1:32 pm
Thanks for your reply,
I still have a doubt: can i make an interpretation about the proporion of cases on each side of the zero (that is the lower bound of th CI divided by the full range)? Or the credibility intervals give only range of the estimate, like confidence intervals?
In other words, do the credibility intervals refer to number of observations or the possible values that the parameter can assume?
 Bengt O. Muthen posted on Monday, December 09, 2013 - 2:02 pm
Credibility intervals are just like confidence intervals.
 Scott R. Colwell posted on Wednesday, August 06, 2014 - 7:23 am
For an multiple group analysis of an ALT Model where the estimator = bayes, I understand that we must use TYPE=MIXTURE and the KNOWNCLASS option.

If I have 2 groups (say gender with 0 and 1) and I do not want to explore classes within gender (only looking at gender differences) then do I set it as follows?

CLASSES = cgender (2) c (1);
KNOWNCLASS = cgender (gender = 0 gender = 1);

Thank you,
 Linda K. Muthen posted on Wednesday, August 06, 2014 - 7:55 am
You can use only a KNOWNCLASS variable:

CLASSES = cgender (2);
KNOWNCLASS = cgender (gender = 0 gender = 1);
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