|
Message/Author |
|
Amrit Nandan posted on Wednesday, September 12, 2007 - 11:22 am
|
|
|
Hi I am working on a very complex model. The details are as follows: # LV's = 15 (each having on an average of about 6 variables of the 5 point rating scale type) Final Destination variable = 1 (another 5 point rating question type) The underlying structure between the LV's leading to the final destination variable can be complex and has quite a lot amount of flexibility. I tried few iterations which leads to results like : df = 2835 CMIN = 10477.5 p = 0.000 RMSEA my model = 0.116 independence model = 0.19 The model is in pretty bad shape. Is there any methodical way of coming to a good model which gives some good underlying business hypothesis to these variables? Or is it that I would have to continue shooting in the dark? |
|
|
I would start out with an EFA of the observed variables for your latent variables to see if the structure you are specifying is even close to fitting the data. |
|
Back to top |
|
|