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Nils Henker posted on Monday, September 26, 2011 - 8:34 am
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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 |
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The first model is just-identified 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. |
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Nils Henker posted on Wednesday, September 28, 2011 - 2:40 am
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Thank you very much. |
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Ann Chen posted on Wednesday, September 28, 2011 - 9:33 am
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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 Chi-Square Test of Model Fit Value 12.217 DF 11 P-value 0.3476 Chi-Square Test of Model Fit for the Baseline Model Value 20.001 DF 20 P-value 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 |
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Please send the full output and your license number to support@statmodel.com. |
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Jordan Gross posted on Wednesday, November 25, 2015 - 1:22 pm
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Hi Dr. Muthen, I have a model with the following specification: VARIABLE: Names are V1-V24; MISSING ARE ALL (-99); CATEGORICAL ARE V5 V6; ANALYSIS: ESTIMATOR= ML; ITERATIONS = 3000; CONVERGENCE = 0.00001; MODEL: precoll BY V1-V4; V2 WITH V1; instemp BY V7-V10; V9 WITH V7; peers BY V11-V13; fit BY V14-V17; V17 WITH V15; attract BY V18-V21; V19 WITH V18; intent BY V22-V24; 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! |
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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. |
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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! |
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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? |
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Model Indirect with Bayes is available in Version 7.4. For your zero beta run, send to support along with license number. |
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Thank you for all of your help. Is there a way to get Model Indirect with ML? |
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When MODEL INDIRECT is not available, you can use MODEL CONSTRAINT. |
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Hello! I am conducting a moderation-mediation 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 individual-level and my question is focused on social-structural 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). Chi-Square Test of Model Fit Value 43.533* Degrees of Freedom 5 P-Value 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! |
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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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