Simon Pickett
2007-Aug-30 16:51 UTC
[R] percentage explained by fixed effects in random model
Hi,
I realise this has come up before in various reincarnations but I couldnt
find the answer...
I wish to quote the "percentage variance explained" by each of three
components in my mixed model.
If I didnt have a random effect I would just use r squared. I can work out
the percentage explained by the random effect using summary() but this
doesnt give variance for the fixed effects.
Linear mixed-effects model fit by REML
Formula: yell ~ carot.code + weight16 + (1 | fosterbrood)
Data: colour
AIC BIC logLik MLdeviance REMLdeviance
1555.455 1576.282 -772.7276 1536.585 1545.455
Random effects:
Groups Name Variance Std.Dev.
fosterbrood (Intercept) 1.0747 1.0367
Residual 1.1363 1.0660
# of obs: 476, groups: fosterbrood, 61
Fixed effects:
Estimate Std. Error DF t value Pr(>|t|)
(Intercept) -3.187028 1.011828 473 -3.1498 0.001737 **
carot.code1 0.201951 0.098442 473 2.0515 0.040771 *
weight16 0.168861 0.054273 473 3.1114 0.001975 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) crt.c1
carot.code1 0.035
weight16 -0.989 -0.084
I was thinking of (cheating by) taking the residuals from a regression
with the random effect (fosterbrood) as a fixed effect, then correlating
these with my two x variables?
Any better ideas?
Thanks in advance, Simon.
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