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. [[alternative HTML version deleted]]