interpreting growth model fitmeasures with "MLR"

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gurkan cuvitoglu

Jul 28, 2019, 7:38:39 PM7/28/19
to lavaan
Hi, i m new to these topics. i m running a basic lgm with 3-4 occasions, unconditional, without missing, n=1055, non-normal data so i m running the "MLR" estimator. 

i m testing effect of sample size (50-100-150-250) combined with different occasions to model fit and statistical power. i m using lsay data. cohort2 math7-8-9-10.

Which one to use: chisq, chisq.scaled, baseline.chisq or baseline.scaled.chisq.

i am confused because of this: 

Model test baseline model:

  Minimum Function Test Statistic               32.016      23.554
  Degrees of freedom                                 3                3
  P-value                                                   0.000            0.000

here lavaan giving measures of baseline. 
But i was thinking to use chisq.scaled. which one i have to use?

i want to ask three more question:
1. i am going to report robust fit indices. is it what to be done?
2. fmin 
   0.003  is this important? how to interpret?

3. i have been reading for weeks about model fit indices. my model is simple as wrote. but every researcher has his/her favourite incices. 
Kenyy says CFI and TLI not suitable with LGM but Muthens, Bollen etc. using these. a
because my data is non-normal i m using mlr but McDonald suggesting to use mfi with small sample size.
so i think to report these:
RMSEA/ RMSEA CI and close fit
nullRMSEA if <0.158
power using -> findRMSEApower(rmsea0, rmseaA , alpha, n, df ) (semTools in R)
reliability(fit) for i, s and total (semTools)
Do these choices make sense? (non-normal and small sample size)
thanks already

Terrence Jorgensen

Aug 6, 2019, 11:35:26 AM8/6/19
to lavaan
I don't see any questions specifically about lavaan. Have you posted your question on the general forum SEMNET?

Terrence D. Jorgensen
Assistant Professor, Methods and Statistics
Research Institute for Child Development and Education, the University of Amsterdam

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