Posted by
Maguin, Eugene on
Apr 04, 2014; 5:49pm
URL: http://spssx-discussion.165.s1.nabble.com/SPSS-Hessian-Matrix-Error-Help-tp5725300p5725314.html
I may be misreading and misunderstanding your mixed statement but I read it to say that you have pure level 1 model, i.e., no level 2 predictors. Your level 1 model is y(I,j) = B0+B1*IW# +e(I,j).
Where B0 an B1 are both random, as you specify. Have you run a model development sequence beginning with a random intercepts model? And did that solve without issues? Which covariance parameter is identified as redundant? The B1 variance or the B1,B2 covariance? Could on or both of these be not significant? What happens if you remove the random effect?
It sounds like you a number of DVs to cycle through this general model. When you look at the within interviewer distributions for this proportion variable, are you satisfied that the data are adequately modeled by a normal distribution rather than a logistic distribution that is available in Genlinmixed?
Gene Maguin
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of Stolz100
Sent: Friday, April 04, 2014 11:58 AM
To:
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Subject: SPSS Hessian Matrix Error - Help!
I am trying to conduct a linear growth model in SPSS using mixed models. We conducted a training study where participants (interviewers) conducted 10 weeks of interviews with children, receiving regular peer-review. Our dependent measures are their questioning techniques, and how they might change over time (e.g. does the proportion of yes-no questions decrease?).
When I run the model in SPSS, I get an error stating the following: The final Hessian matrix is not positive definite although all convergence criteria are satisfied. The MIXED procedure continues despite this warning.
Validity of subsequent results cannot be ascertained.
In addition, on the estimates of covariance parameters, I get the following
error: This covariance parameter is redundant. The test statistic and confidence interval cannot be computed.
I have tentatively conducted a one-way ANOVA to assess whether there is level 2 variation in my predictor, and there is. This was significant at p < .001.
I am unsure why I am receiving the current error for the growth model and would like to solve the problem. Here is my syntax:
Please help!
MIXED YN_Proportion WITH Interview_Number
/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1)
SINGULAR(0.000000000001) HCONVERGE(0,
ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)
/FIXED=Interview_Number | SSTYPE(1)
/METHOD=ML
/PRINT=CPS CORB DESCRIPTIVES SOLUTION TESTCOV
/RANDOM=INTERCEPT Interview_Number | SUBJECT(Participant) COVTYPE(ARH1).
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