[R-sig-ME] vif using GLMMadaptive

[Ben Bolker]

     My advice would be to sort out the underlying problem (which is 
*not* at all related to mixed models)   and not move to mixed models in 
the hope that that will fix something.  I believe (but am not sure) that 
you're using vif() from the car package?

    * you may be able to un-alias your variables by eliminating the 
'main effect' terms in your model;  in R formula syntax,  A*B is 
equivalent to  1+A+B+A:B.  So dropping the main effects that are already 
included in the * terms, or switching from * to : for interactions, may 
solve your problem.

On 5/1/20 2:12 AM, Matos, Grisenia wrote:
> I am a PhD student and am working on a school  project due over the weekend.  I ran the following regression:
> spending.REG <- glm.nb(spending_count ~ conservative + liberal + moderate + trust_gov + liberal*trust_gov + conservative*trust_gov + moderate*trust_gov + income + education + age + female + white + budget_difficult + democrat + republican, data = Trustdata1)
>
> I attempted to get a vif score and got this error in R Studio: there are aliased coefficients in the model
>
> The variables conservative, liberal and moderate are fixed effect where they are either 0 or 1.  The female variable is a 0 or 1.  There are three interactive variables:  moderate*trust_gov, liberal*trust_gov, and conservative*trust_gov.  Moreover, moderate and moderate*trust_gov are the base variables.
>
> I would like to calculate the vif for the regression equation.  First, in order to get rid of the error and thereafter calculate the vif scores, I attempted to use your code:
>
> library("GLMMadaptive")
>
> fm <- mixed_model(y ~ time + sex, random = ~ 1 | id, data = <your_data>,
> family = zi.negative.binomial(), zi_fixed = ~ sex, zi_random = ~ 1 | id)
>
> it returned an error: unexpected '=' in: "erate + trust_gov + liberal*trust_gov + conservative*trust_gov + moderate*trust_gov + income + education + age + female + white + budget_difficult + democrat + republican, random = 1 | id, dat
>                    +                   family ="
>
> Please provide guidance as to what I am doing incorrectly.  I appreciate your help.
>
> Thanks,
>
> Grisenia
>
>
>
>
>
> 	[[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models