Anonymous posted on Tuesday, April 01, 2003 - 6:10 pm
I have three annual assessments of two variables for husbands and wives from 71 couples: ratings of frequency of child problems (h8t-h10t for husbands and w8t-w10t for wives)and parenting satisfaction (h8psat-h10psat for husbands and w8psat-w10psat for wives). There are missing data. Because I know that there is no growth for either variable, I want to examine the intra- and cross-parent relation between averaged parenting satisfaction and averaged ratings of child problems for each parent over the 3 assessments. I want errors for husbands' ratings of child problems and wives' ratings of child problems to correlate. Here is my MPLUS syntax:
USEVARIABLES ARE h8t-h10t h8psat-h10psat w8t-w10t w8psat-w10psat; MISSING ARE ALL (-99); ANALYSIS: TYPE = MISSING H1; ITERATIONS=5000; H1ITERATIONS=5000; MODEL: hit BY h8t-h10t@1; hipsat BY h8psat-h10psat@1; wit BY w8t-w10t@1; wipsat BY w8psat-w10psat@1; hit ON hipsat wipsat; wit ON hipsat wipsat;
Here is selected output: Chi-Square Test of Model Fit
Value 101.594 Degrees of Freedom 56 P-Value 0.0002
Chi-Square Test of Model Fit for the Baseline Model
Value 383.150 Degrees of Freedom 66 P-Value 0.0000
My question involves the stated 56 degrees of freedom for the chi-square test of model fit. There are 12 observed scores, giving (12x13)/2 = 78 parameters. The output says I have 34 free parameters, and the tech1 output confirms this:
I would think this model would give me 78-34=44 degrees of freedom, but I get 56 df. P. 36 of the manual says that MEANSTRUCTURE is included by default in MISSING analyses. Am I correct in assuming that the discrepancy between the reported 56 df and the expected 44 df is that the intercept parameters (NU 1-12) are not really included as parameters?
I ran the problem in LISREL 8.53 and get nearly identical results with 56 df and no intercept parameters.
The means are both part of your sample statistics and also part of your estimates. Note that there are twelve free parameters in the nu matrix. So your sample statistis are 78 + 12 = 90 - 34 = 56. If you ran the problem without means, you would have 78 - 22 = 56. Please let me know if this does not answer your question.
Anonymous posted on Wednesday, April 02, 2003 - 5:32 pm
I can easily get the analysis I want (without means) by dropping the TYPE=MISSING entry in the ANALYSIS section. How can I use the MISSING option and run the problem without means? I have tried setting the intercepts and means of the latent variables to 0, get the identification of the estimated parameters I want, but the estimates themselves are off. Is this a scaling issue?
You cannot run the MISSING analysis without means. Means are required for this estimation. However, having unstructured means as part of the model does not affect the results. These means are estimated as the sample values. You can try this out without missing to show yourself. Fixing the means to zero is not correct.
Anonymous posted on Wednesday, April 02, 2003 - 9:27 pm
Thank you. I now see that the structure of the output from Mplus and LISREL differs because Mplus requires the means for estimation. Parameter estimates themselves are nearly identical in the two programs.