[R] publishing random effects from lme
Christoph Scherber
Christoph.Scherber at uni-jena.de
Wed Feb 2 09:58:16 CET 2005
Dear all,
Suppose I have a linear mixed-effects model (from the package nlme) with
nested random effects (see below); how would I present the results from
the random effects part in a publication?
Specifically, I´d like to know:
(1) What is the total variance of the random effects at each level?
(2) How can I test the significance of the variance components?
(3) Is there something like an "r squared" for the whole model which I
can state?
The data come from an experiment on plant performance with and without
insecticide, with and without grasses present, and across different
levels of plant diversity ("div").
Thanks for your help!
Christoph.
lme(asin(sqrt(response)) ~ treatment + logb(div + 1, 2) + grass,
random = ~ 1 | plotcode/treatment, na.action = na.exclude, method = "ML")
Linear mixed-effects model fit by maximum likelihood
Data: NULL
AIC BIC logLik
-290.4181 -268.719 152.209
Random effects:
Formula: ~ 1 | plotcode
(Intercept)
StdDev: 0.04176364
Formula: ~ 1 | treatment %in% plotcode
(Intercept) Residual
StdDev: 0.08660458 0.00833387
Fixed effects: asin(sqrt(response)) ~ treatment + logb(div + 1, 2) + grass
Value Std.Error DF t-value p-value
(Intercept) 0.1858065 0.01858581 81 9.997225 <.0001
treatment 0.0201384 0.00687832 81 2.927803 0.0044
logb(div + 1, 2) -0.0203301 0.00690074 79 -2.946073 0.0042
grass 0.0428934 0.01802506 79 2.379656 0.0197
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-0.2033155 -0.05739679 -0.00943737 0.04045958 0.3637217
Number of Observations: 164
Number of Groups:
plotcode ansatz %in% plotcode
82 164
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