[R] Random structure of nested design in lme

From: ESCHEN Rene <rene.eschen_at_unifr.ch>
Date: Wed 19 Jul 2006 - 21:36:45 EST


All,

I'm trying to analyze the results of a reciprocal transplant experiment using lme(). While I get the error-term right in aov(), in lme() it appears impossible to get as expected. I would be greatful for any help.

My experiment aimed to identify whether two fixed factors (habitat type and soil type) affect the development of plants. I took soil from six random sites each of two types (arable and grassland) and transplanted them back into the sites of origin in such way that in each of the sites there were six pots containing arable soil and six pots of grassland soil, each containing a seedling.

With aov(), I got the analysis as I expected, with habitat type tested against destination site, and soil type tested against origin site:

summary(aov(response~soiltype*habitat+Error(destination+origin)))
#
#Error: destination
# Df Sum Sq Mean Sq F value Pr(>F)
#habitat 1 1.0000 1.0000 0.699 0.4226
#Residuals 10 14.3056 1.4306
#
#Error: origin
# Df Sum Sq Mean Sq F value Pr(>F)
#soiltype 1 1.77778 1.77778 11.636 0.006645 **
#Residuals 10 1.52778 0.15278
#---
#Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#
#Error: Within
# Df Sum Sq Mean Sq F value Pr(>F)
#soiltype:habitat 1 0.2500 0.2500 2.1774 0.1427
#Residuals 120 13.7778 0.1148

However, when I try to replicate this analysis in lme, I am unable to get the structure of the random factors (origin and destination) correct. Does anyone have a suggestion how to resolve this problem?

Thanks in advance.

René Eschen

CABI Bioscience Centre Switzerland
Rue des Grillons 1
2800 Delémont
Switzerland

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