Message/Author 

EFried posted on Tuesday, April 02, 2013  3:45 pm



Dear Prof Muthens, I am aiming to investigate whether the effects of a number of risk factors (x) are differentially associated with various medical symptoms (y). Correlations among x, and correlations among y, are moderate to high (0.20.6). Correlations between x and y are low (maximum 0.2). I want to compare two models: one in which the effects of all x on all y are freely estimated, and one in which the effects are constrained (see example below). Model I: y1 ON x1 x2; y2 ON x1 x2; Model II: y1 ON x1 (1); y1 ON x2 (2); y2 ON x1 (1); y2 ON x2 (2); (1) I want to allow for correlations between all x. Is x1 x2; the right way to do this? Does it have consequences regarding if model I or model II is preferred? (2) The unconstrained model has perfect fit (e.g., with 4y and 7x and 42 DF). Is that a sign that something might be wrong with the model? (3) What test do I perform to compare Model I and Model II  is it correct to use Thank you 

EFried posted on Tuesday, April 02, 2013  3:48 pm



sorry, (3) should read: "What test do I perform to compare Model I and Model II  is it correct to use a LLH test? 


1. The correlations among the x's are free as the default without mentioning their means, variances, or covariances. 2. If you have 42 df and perfect fit, something strange is going on. Also, Model I looks like it has 0 df. Perhaps you are inadvertently uncorrelating the x's; check your output. 3. A likelihoodratio chi2 test comparing Model I and II is fine. I don't know what a LLH test is. 

EFried posted on Tuesday, April 02, 2013  4:50 pm



Bengt, thank you very much for the quick answer. Running a simplified model with much fewer variables: MODEL: d_s1_m ON Sex; d_s1_m ON ZNeuro; d_s3_m ON Sex; d_s3_m ON ZNeuro; This results in the perfect fit summarized below. What am I missing? Thank you! 9 DF LLH H0 2940.091 LLH H1 2940.091 AIC 5898.182 BIC 5945.495 ChiSquare Test of Model Fit Value 0.000 Degrees of Freedom 0 PValue 0.0000 RMSEA (Root Mean Square Error Of Approximation) Estimate 0.000 90 Percent C.I. 0.000 0.000 Probability RMSEA <= .05 0.000 CFI/TLI 1.000 ChiSquare Test of Model Fit for the Baseline Model Value 164.887 Degrees of Freedom 5 PValue 0.0000 SRMR (Standardized Root Mean Square Residual) Value 0.000 


You model has zero degrees of freedom. ChiSquare Test of Model Fit Value 0.000 Degrees of Freedom 0 PValue 0.0000 Model fit cannot be assessed for a model with zero degrees of freedom. 

EFried posted on Wednesday, April 03, 2013  10:49 am



Thank you. When running 10 regressions in MPLUS as listed above, allowing all variables to correlate with each other, do I need to adjust for typeI error manually, or does MPLUS do that automatically? 


No. 

EFried posted on Sunday, April 07, 2013  10:09 am



Sorry  "No." regarding "do I need to adjust for typeI error manually", or "No." regarding "or does MPLUS do that automatically"? Thank you 


No, nothing needs to be done. 

EFried posted on Sunday, April 07, 2013  12:14 pm



Great, thank you! 

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