Stacia,The covariance between the random components should not be redundant. Given the message you are receiving, I suspect that the variable you believe to represent "week" is in fact equal to your subject identification variable. Are you 100% certain this is not the case?The dataset should be structured in long format as follows:ID week1 01 11 21 3...2 02 12 22 3...Please write back confirming that you have not inadvertently made the mistake I mentioned above and that your dataset is structured as I have illustrated.RyanOn Fri, Apr 4, 2014 at 5:45 PM, Stolz100 <[hidden email]> wrote:
Hi. Children's responses are proportions ranging from .00 - 1.00. Interview number is the week number, ranging from the 1st interview at week 1 to the 10th interview at week 10.The ARH1 rho covariance is identified as redundant. If I remove the random effect for interview number (week), then the model runs just fine.
The data seem normally distributed across the three dependent measures that I need to conduct growth curves for (proportion of: yes-no questions, "Wh" questions, open-invitation questions).Thank you two so much for thinking through this with me! I've never actually conducted a GENLINMIXED so if that is what is necessary I would appreciate any tutorials or academic resources you recommend regarding that analysis.Warm regards,StaciaOn Fri, Apr 4, 2014 at 2:28 PM, Ryan Black [via SPSSX Discussion] <[hidden email]> wrote:
1. Your response is binomial, so GENLINMIXED is preferred.2. Please define what Interview_Number means. I was expecting to see "week" as the random slope.RyanOn Fri, Apr 4, 2014 at 11:58 AM, Stolz100 <[hidden email]> wrote:
[hidden email] (not to SPSSX-L), with no body text except theI 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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