
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
 		 	   		  
	[[alternative HTML version deleted]]


