Message/Author 

Nils Henker posted on Monday, September 26, 2011  8:34 am



Hallo, i conducted a path analysis with Mplus. I used this syntax: model: B on A; C on AB; E on ABC; model indirect: A ind B A; E ind C B A; This model had a perfect fit. Then I added a second mediator for the relation between B and E. I used this syntax: model: B on A; C D on AB; E on ABCD; model indirect: C ind B A; D ind B A; E ind C B A; E ind D B A; Now the model fit indices are really bad. Does anyone know why the model fit droped from perfect to very bad just because I added a second mediator? Best regards, Nils 


The first model is justidentified so model fit is not relevant. The second model has one degree of freedom. Leaving out that path causes the model not to fit the data. 

Nils Henker posted on Wednesday, September 28, 2011  2:40 am



Thank you very much. 

Ann Chen posted on Wednesday, September 28, 2011  9:33 am



Dear Dr. Muthén, I have a multiple mediations model with zero CFI and negative TLI. I'm not sure what does this mean? Poor model fit? But I got aceeptable RMSEA and SRMR. The following is the tests of model fit: TESTS OF MODEL FIT ChiSquare Test of Model Fit Value 12.217 DF 11 Pvalue 0.3476 ChiSquare Test of Model Fit for the Baseline Model Value 20.001 DF 20 Pvalue 0.4579 CFI/TLI CFI 0.000 TLI 2009.133 RMSEA Estimate 0.029 SRMR Value=0.051 I appreciate any comments and suggestions. Thank you. Best, Ann 


Please send the full output and your license number to support@statmodel.com. 

Jordan Gross posted on Wednesday, November 25, 2015  1:22 pm



Hi Dr. Muthen, I have a model with the following specification: VARIABLE: Names are V1V24; MISSING ARE ALL (99); CATEGORICAL ARE V5 V6; ANALYSIS: ESTIMATOR= ML; ITERATIONS = 3000; CONVERGENCE = 0.00001; MODEL: precoll BY V1V4; V2 WITH V1; instemp BY V7V10; V9 WITH V7; peers BY V11V13; fit BY V14V17; V17 WITH V15; attract BY V18V21; V19 WITH V18; intent BY V22V24; V5 V6 ON precoll; fit ON V5 V6 instemp peers; attract ON fit; intent ON precoll attract; 1. What is the best method to estimate my model given that I have missing data and both categorical and continuous variables? 2. When I ran the model, it did not produce model fit statistics and it said that it couldn't produce MODINDICIES because of the binary variable. Is there a way to gather this information? 3. I would like to estimate indirect, direct, and total effects between all of the variables. What is the best way to do that? What would I have to include beside IND or VIA statements? Any help would be greatly appreciated! 


1. ML or Bayes. See also our FAQ: Estimator choices with categorical outcomes 2. Fit and Modind are only obtained using WLSMV. Fit is obtained also with Bayes. 3. Model Indirect with IND and VIA should do it. 


Hi Dr. Muthen, Thank you for your helpful response. I tried using both ML and Bayes estimation methods and received the following error messages: *** ERROR MODEL INDIRECT is not available for analysis with ALGORITHM=INTEGRATION. *** ERROR MODEL INDIRECT is not available for analysis with ESTIMATOR=BAYES. How can I avoid getting this message? Thank you! 


Also, when I ran the model using ML without the model indirect commands, all of the Betas were 0.000. Is there a way to get path coefficients when there are continuous and categorical variables in the model? 


Model Indirect with Bayes is available in Version 7.4. For your zero beta run, send to support along with license number. 


Thank you for all of your help. Is there a way to get Model Indirect with ML? 


When MODEL INDIRECT is not available, you can use MODEL CONSTRAINT. 


Hello! I am conducting a moderationmediation path analysis and building a model with a binary exposure, a binary outcome, 2 binary mediators, and 1 binary moderator. I am also adjusting for 4 confounders. I am using longitudinal data and my sample has 466 individual clusters and a total of ~ 2000 observations over time. One of the confounders I am adjusting for is also hypothesized to be on causal path however, from a theoretical perspective it is not a mediator of interest to my research question since it is at the individuallevel and my question is focused on socialstructural mediators. When I remove this confounder/mediator from my model and do not adjust for it, the hypothesized indirect mediated pathways are strongly significant. When I adjust for it, pathways are only marginally significant at best. Fit indices for model where I do not adjust the coufounder are below. RMSEA looks ok but TLI is negative (see more below). ChiSquare Test of Model Fit Value 43.533* Degrees of Freedom 5 PValue 0.0000 RMSEA Estimate 0.064 90 Percent C.I. 0.048 0.082 Probability RMSEA <= .05 0.079 CFI/TLI CFI 0.715 TLI 0.196 Do you have any suggestions? Thank you! 


We need to see the relevant outputs  send to Support along with your license number. Note also that mediation with binary DVs call for special considerations as explained on our Mediation web page under counterfactual effects. 

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