Hi all,
I’m currently working on a dataset and struggling to properly set up a repeated-measures linear mixed model in SPSS, and I would greatly appreciate your guidance.
In my study, the dependent variable is jump performance. Each participant has four repeated measurements, resulting from a combination of two factors:
• Time: pre and post intervention
• Leg: dominant and non-dominant
So for each subject, I have:
• pre-dominant
• pre-non-dominant
• post-dominant
• post-non-dominant
These conditions are stored in two separate columns: one indicating the leg (dominant vs. non-dominant) and one for time (pre vs. post). My aim is to evaluate whether a specific type of training intervention had an effect on jump performance, considering both leg and time as repeated factors. The variable "codice" is the code (so the subjects). When i insert subjcet as random effect, with intercept i have problem. The output say:
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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.
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This is the syntax
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MIXED HOPPING BY DOM0NODOM1 PRE0POST1
/CRITERIA=DFMETHOD(RESIDUAL) CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001)
HCONVERGE(0.00000001, RELATIVE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0, ABSOLUTE)
/FIXED=DOM0NODOM1 PRE0POST1 DOM0NODOM1*PRE0POST1 | SSTYPE(3)
/METHOD=REML
/PRINT=SOLUTION TESTCOV
/RANDOM=INTERCEPT | SUBJECT(CODICE) COVTYPE(VC)
/REPEATED=DOM0NODOM1*PRE0POST1 | SUBJECT(CODICE) COVTYPE(CS)
/EMMEANS=TABLES(DOM0NODOM1) COMPARE ADJ(BONFERRONI)
/EMMEANS=TABLES(PRE0POST1) COMPARE ADJ(BONFERRONI)
/EMMEANS=TABLES(DOM0NODOM1*PRE0POST1) .
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Could someone help me please?
