[R-sig-ME] Problem_Downdated VtV is not positive definite

[Ben Bolker]

On 2020-01-19 8:29 a.m., C. AMAL D. GLELE wrote:
> Hello, everyone.
> In the models below, mydata has 32 rows
> village and Year are grouping factor variables with respectively 8 and 4
> levels.
> 1)
> model1.1 fits well
> model1.1<-glmer(cbind(F,L)~village+Year+(1|Year)+(1|village),
> family="binomial",data=mydata)
> But, when I replace village+Year by village*Year, I get the warning and
> error message below
> model1.2<-glmer(cbind(F,L)~village*Year+(1|Year)+(1|village),
> family="binomial",data=mydata)
> Warning:
> fixed-effect model matrix is rank deficient so dropping 2 columns /
> coefficients
> Error message:
> Error in (function (fr, X, reTrms, family, nAGQ = 1L, verbose = 0L, maxit =
> 100L,  :
>   Downdated VtV is not positive definite

   When you include a fixed effect of village*Year, it expands to (1 +
village + Year + village:Year).

  Assuming Year is numeric, the combination of a fixed effect of Year
(treated as the overall slope of a linear relationship) and a random
intercept of Year (Year treated as a categorical grouping variable) is OK.

  But ... you also have village as categorical fixed effect *and* a
random intercept, which is redundant.

   You could use  ~ Year + village:Year  + (1|Year) + (1|village) *or*
                  ~ Year + (1+Year|village)



> I noticed a similar behavior when trying with glmmadmb:
> model2.1 fits well
> model2.1<-glmmadmb(cbind(F,L)~village+Year+(1|Year)+(1|village),family="binomial",data=na.omit
> 
> (mydata))
> But, with village*Year, Iget the error message below:
> model2.2<-glmmadmb(cbind(F,L)~village*Year+(1|Year)+(1|village),family="binomial",data=na.omit
> 
> (mydata))
> Error:
> Error in glmmadmb(cbind(F, L) ~ village * Year + (1 | Year) + (1 |
> village),  :
>   rank of X = 30 < ncol(X) = 32
> ##
> in advance, thanks for helping solve these issues(I'm very interested in
> interaction terms).
> Kinds regards,
> 
> 	[[alternative HTML version deleted]]
> 
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