[R-sig-ME] Interpreting and making sense of the variance in random effects with glmm in nlme

Sharada Ramadass @h@r@d@@r@m@d@@@ @ending from gm@il@com
Fri May 25 13:48:22 CEST 2018

  I am new to glmm and I am trying to use a mixed model for my data. I have
explanatory variables that are fixed effects, such as individual organism
measurement data, biotic and abiotic factors (both at different spatial
I also have 13 species and 15 individuals per species and have incorporated
them as random effects (with individuals nested within species in an
intercept model).

However, I am not clear as to how to interpret the random effects variance
components and how they relate to the total variance explained by the
random factors in the model.

Here's an example output snippet.

Random effects:

 Formula: ~1 | species


StdDev:   0.2443396

 Formula: ~1 | indv %in% species

         (Intercept)  Residual

StdDev: 4.502529e-05 0.5041833

How do I interpret this output? Any inputs would be appreciated.

Thanks and Regards,

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