# [R-sig-ME] Calculating SE from GLMM results (using glmer{lme4})

Raldo Kruger raldo.kruger at gmail.com
Thu Sep 24 08:05:32 CEST 2009

```Dear R users,

Please excuse the basic questions, but I’m new to GLMMs and R!

I’m analyzing an experiment where Seedling numbers in plots where seed
has been sown on restoration sites is the response variable. I’m most
interested in determining whether the Nutrients (N) and water
absorbing polymer Gel (Ge) additions to the soil substrate contribute
positively to the survival of the seedlings, over a 3 year time period
(for simplicity I'm just using 3 time periods, each in the same season
for the 3
successive years).
Fixed factors: Nutrients (0 and 1), Gel (0 and 1)
Random factors: Site (4 non replicate sites), Year (3 time periods)
Response variable: Seedling numbers (counts) / 0.25m2 plot
The results are as follows:
Estimate	Std. Error	z value	 Pr(>|z|)
(Intercept)	4.52982	0.24486	18.5	       <2.00E-16	***
N	       -0.07922	0.08415	-0.94	       0.346489
Ge	         0.20766	0.08428	2.46	        0.013744	*
Year  	-1.62937	0.04672	-34.88	<2.00E-16	***
N:Ge 	-0.44213	0.11898	-3.72   	0.000202	***
N:Year	0.11705	0.06322	1.85   	0.064125	.
Ge:Year	-0.04861	0.0645	-0.75  	0.451132
N:Ge:Year	0.11458	0.08917	1.28  	0.198821

1)	So as I understand (from previous correspondence with R-users) the
number of seedlings in the control plots in year 0 is
exp(4.53) = 92.7. Is the standard error calculated with
0.24486 (i.e. 92.7*0.24), or with 92.7*exp(0.24).
2)	And for the N:Ge treatment, the effect is exp(-0.08+0.21-0.44)
=0.73 (I.e. a 27% reduction compared to the control), right? So
is the SE for the N:Ge effect calculated as the sum of the
SE’s too, i.e. 0.08+0.08+0.12, or is it just 0.12?
3)	Lastly, is it possible to fit two response variables in one GLMM?
E.g. seedling numbers and height.

Many thanks,
Raldo Krüger
Msc student
University of Cape Town

--
Raldo

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