[R-sig-ME] intra-class correlation coeff
bates at stat.wisc.edu
Fri Jan 23 21:57:27 CET 2009
I saw Andrew Tyne's reply and agree with what he said.
Another way of approaching this is to realize that you only have 3
distinct levels of market. That's in the area where you probably are
better off modeling it as a fixed-effects term, rather than a
random-effects term. It may make sense logically to regard it as a
random effect but practically it is difficult to estimate a variance
from only a few observations. We can get an estimate but often it has
very poor precision.
I would suggest modeling it as a fixed effect and seeing if the term
is significant there.
On Fri, Jan 23, 2009 at 4:33 AM, Metras, Raphaelle <rmetras at rvc.ac.uk> wrote:
> I am a very beginner with R and mixed-models, so please apologize if you
> think my questions are naive.
> I am fitting a glmer Poisson, with one variable as random effect
> (market) and 2 variables as fixed effects.
> My observations are clustered markets, there are 3 markets.
> When looking at the variance of the random effect, and it is close to
> zero (0.07484).
> I would like to know if it is possible to extract the intra-class
> correlation coefficient somehow, or if knowing the between market
> variance (0.07484) is enough to say that there is almost no clustering.
> Thank you very much, I copy the ouput below:
> Generalized linear mixed model fit by the Laplace approximation
> Formula: clear_bsk ~ dist_mkt + same_trader + offset(log(no_bsk)) + (1 |
> Data: essai
> AIC BIC logLik deviance
> 55.9 63.39 -23.95 47.91
> Random effects:
> Groups Name Variance Std.Dev.
> market (Intercept) 0.07484 0.27357
> Number of obs: 48, groups: market, 3
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) -1.34246 0.32716 -4.103 4.07e-05 ***
> dist_mkt -0.02948 0.01380 -2.137 0.032639 *
> same_traderY 0.99278 0.27366 3.628 0.000286 ***
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> Correlation of Fixed Effects:
> (Intr) dst_mk
> dist_mkt -0.546
> same_tradrY -0.656 0.282
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