TITLE: Montecarlo of snap; DATA: FILE = "z:\projects\snap archive\boot.txt"; TYPE = MONTECARLO; VARIABLE: NAMES = y1-y285; categorical are y1-y285; MISSING = .;
ANALYSIS: TYPE = efa 1 2;
The job runs through the (currently 3) datasets that I specify, but the output doesn't contain anything about the EFA, it ends after computing the correlation matrix. TECH9 lists each iteration, but no errors. I also note that each dataset runs fine on its own.
Linda, by way of follow-up, I thought I might try the same problem using the Mplus monte carlo data generation rather than doing it internally. That would entail running a step one model to simply estimate all 285 thresholds, which could then be used as the basis for a monte carlo run using the population statement.
I guess my question is, how can I run a model to do nothing but estimate and save the thresholds for a whole lot of categorical variables?
dear prof I want to generate Monte Carlo data sets using an external program and then model them in MPLUS. all of my repetition are in one datasheet,But I think MPLUS cannot understand them and I should shift every simulation to one datasheet? this is true? thanks
As far as I understand the answers I’ve seen on the discussion boards, it is possible to use the DEFINE command to create an interaction in the second step of an external Monte Carlo simulation. However, because the data are not defined with an interaction set as a population parameter (i.e. with the MODEL POPULATION command), then the interaction will not actually be present in the simulated data. Is that correct?
If I understand the description on that linked pdf correctly, the model is ONLY mathematically equivalent to a standard linear regression with a product term if the residual for the equation of the slope of x’s effect on M is set to 0. Is that correct?
Second, does anything in the syntax from that document, such as perhaps TYPE=RANDOM, need to be changed to make the analysis mathematically equivalent to a traditional moderation analysis using a product term?