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?
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)