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Marie Alice posted on Monday, November 24, 2014 - 10:55 pm
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I am trying to run multi-group analyses, to see whether the path coefficients differ by groups. (I only have observed variables in the model.) As step 1, I ran separate models for two groups. As step 2, I ran the two groups together with unequal path coefficients.It seemed to run okay until here. However, as step 3, I tried to run two groups together setting the path coefficients to be equal to compare the Chi-square statistics with the previous model, and I got an error message. variable: names = ses score single urban_r income feduc meduc; usevariables = single score income; missing = all(9999); grouping=urban_r(0=rural 1=urban); analysis: type = general; estimator = ML; model is nomeanstructure; model: score on income single(1-2); income on single(3); model indirect: score ind income single(4); model rural: output: stand(STDYX) mod(all); error message: *** WARNING in ANALYSIS command MODEL=NOMEANSTRUCTURE is not allowed in conjunction with TYPE=MISSING. Request for MODEL=NOMEANSTRUCTURE will be ignored. *** ERROR in MODEL INDIRECT command There must be 2 values given with the IND statement representing the X and X* values. Problem with: SCORE IND SINGLE I would greatly appreciate your help. |
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You must include means in the model. You cannot use labels in MODEL INDIRECT. (4) cannot be included. |
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Marie Alice posted on Tuesday, November 25, 2014 - 10:33 pm
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Linda, Thank you very much for your response. The model ran okay without the "model is nomeanstrucutre" and the (4) after the model indirect. One additional question. To compare the chi-square statistics across two models, for the model without equal constraints, I get df=0, value=0. But for the model with equal constraints, I get df=3,and value=17.174. 1. Why is df=0? my sample size is 14383, and I only have three parameters in the model as shown below.(The model should not be saturated.) model: score on income single; income on single; model indirect: score ind income single; 2. Can I subtract these two chi-square statistics (even if one is zero) to see which model fits better? Once again, thanks for bearing with my introductory questions. |
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1. Please send the output and your license number to support@statmodel.com. 2. Yes. |
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