[R-sig-ME] vif using GLMMadaptive
Gr|@en|@@M@to@ @end|ng |rom utd@||@@@edu
Fri May 1 08:12:31 CEST 2020
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:
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.
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