[R-lang] Re: Effect size in linear mixed effects models

[Levy, Roger]

Hi Zhenguang,

I am not familiar with exactly what JEP:G asks for, but if you're dealing with continuous predictors, I suggest you keep in mind that in general such predictors have units (e.g., milliseconds for time; # characters for word length; log parts per million for word frequency; bits, nats, or bans for log probability).  If your predictor has units of type S and your response variable has type T, then you could say, for example, "effect size: 10 T/S".  If you are doing a mixed logit model, then the response unit is the logit, so you could say, e.g., "effect size: 2 logits per S".

If you're talking about a categorical predictor, then you want to standardize the contrast to be size 1.  So, for example, code a 2-level predictor as (-0.5,0.5) and then report the parameter estimate associated with the predictor.  Or you could code it as (-1,1) and report the parameter estimate divided by two.

Best & hope this helps,

Roger

On Jul 17, 2013, at 12:01 PM, Zhenguang Cai <zhenguangcai@gmail.com> wrote:

> Hi,
> 
> Some journals (JEP:G) requires effect sizes in the data analysis. I wonder how to do this in LME. Can I just scale the predictors (z-scores, if I understand it correctly) and then use the coefficient as a measure of effect size? Or is there a more standard way to do it?
> 
> Thanks,
> Zhenguang
> 
> -- 
> Zhenguang G. Cai
> 
> Research Fellow
> Institute of Cogntion/ School of Psychology
> University of Plymouth
> Portland Square, Drake Circus, Plymouth, PL4 8AA
> 
> 
> https://sites.google.com/site/zhenguangcai/