[R-sig-ME] standardized coefficients in glmer model

[David Duffy]

On Sat, 11 Dec 2010, Leeuwen, Casper van wrote:

> model <- glmer (intact_binomial ~
>              species
>              + sex
>              + retention_time
>              + body_mass
>              + body_mass * retention_time
>              + (1 | individual)
>              , family = binomial (link = "logit")
>              )
> summary(model)
>
> summary() returns effects sizes given as coefficients of the different 
> factors. However, I would like to indicate the importance of the 
> different terms in the model, to determine the relative importance of 
> for instance sex versus body_mass: which one is more important in 
> explaining my dependent variable?

Given this is a logistic regression, there are various more or less 
unsatisfactory equivalents of an R2.  You might be better off just 
comparing effect sizes eg odds ratio (exp(beta)) for sex versus that for 
the difference between the first and third quartiles of BMI or
from say BMI=20 to BMI=25 and BMI=30, presuming this is human data.

-- 
| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v