Attachment | Size |
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model.R [6] | 2.79 KB |
Models.pdf [7] | 19 KB |
path input alt1.csv [8] | 707 bytes |
I have a data set with six binary variables, which I am trying to determine the temporal relationship. I was using lavaan R package, where they suggested to use dummy variable for endogenous variables (independent) and use ordered for exogenous (dependent variables). I was using the model as described in pdf file. I have gotten following results:
lavaan (0.5-16) converged normally after 31 iterations
Number of observations 51
Estimator DWLS Robust
Minimum Function Test Statistic 5.699 7.295
Degrees of freedom 7 7
P-value (Chi-square) 0.575 0.399
Scaling correction factor 1.006
Shift parameter 1.632
for simple second-order correction (Mplus variant)
Model test baseline model:
Minimum Function Test Statistic 61.153 45.447
Degrees of freedom 14 14
P-value 0.000 0.000
User model versus baseline model:
Comparative Fit Index (CFI) 1.000 0.991
Tucker-Lewis Index (TLI) 1.055 0.981
Root Mean Square Error of Approximation:
RMSEA 0.000 0.029
90 Percent Confidence Interval 0.000 0.153 0.000 0.178
P-value RMSEA <= 0.05 0.654 0.486
According to lavaan since it was using DWLS, AIC and BIC are calculated. However, we had someone analyze the data before for us was using AIC and BIC to compare which temporal relationship is better at explaining our data. So I decided to try OpenMx, I am very new to path analysis and OpenMx, so I am not quite sure if I am treating the variables correctly. I have attached the code and dataset and the model was run and gave me some estimates, however, RMSEA was not computed. And the estimates for each path was different compared to lavaan. At this point, I am not sure how to compare my results from these two methods and if it's even comparable since OpenMx I turned everything into ordinal but in lavaan I used dummy variables. And why is that OpenMx didn't calcualte RMSEA for categorical data.
rl