-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces at r-project.org
[mailto:r-sig-mixed-models-bounces at r-project.org] Namens Lim Yonghao
Verzonden: woensdag 6 april 2011 15:39
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] (no subject)
Dear all,
I wish to conduct a piecewise growth model in a dataset
(n=40) with 9 timepoints. The dependent variable is
vocabulary size. Initially, i ran 3 models (using glmer with
family = poisson) comparing models with a linear growth and
knots at 2 different timepoints. The knots are suggested both
by theory and graphical observation. The models ran
successfully and i chose the model with the lowest AIC.
However, when i added level 2 predictors to the model, the
following error message came up
model2 <- glmer(vocab ~ time1_18*seg + time2_18*seg +
(time1_18 + time2_18|id), data = growth, family = poisson)
Warning messages:
1: In mer_finalize(ans) :
Cholmod warning 'not positive definite' at
file:../Cholesky/t_cholmod_rowfac.c, line 432
2: In mer_finalize(ans) :
Cholmod warning 'not positive definite' at
file:../Cholesky/t_cholmod_rowfac.c, line 432
3: In mer_finalize(ans) : false convergence (8)
I did a brief search of the archives and it seems to suggest
that having a small sample size might result in this. I am
unsure what is causing this. Any advice on how to resolve this?
Cheers,
Yonghao
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