Hello R-help,
I'm studying an example in the R book.
The data file is available from the link
below.http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/fertilizer.txt
Could you explain Why the results from lme() and lmer() are different in the
following case? In other examples, I can get the same results using the two
functions, but not here...
Thank you.Miya
library(lme4)library(nlme)# object dat contains the data
> summary(lme(root~fertilizer,random=~week|plant,data=dat))Linear mixed-effects
> model fit by REML Data: dat AIC BIC logLik 171.0236 183.3863
> -79.51181
Random effects: Formula: ~week | plant Structure: General positive-definite,
Log-Cholesky parametrization StdDev Corr (Intercept) 2.8639832
(Intr)week 0.9369412 -0.999Residual 0.4966308
Fixed effects: root ~ fertilizer Value Std.Error DF
t-value p-value(Intercept) 2.799710 0.1438367 48 19.464499
0e+00fertilizercontrol -1.039383 0.2034158 10 -5.109645 5e-04 Correlation:
(Intr)fertilizercontrol -0.707
Standardized Within-Group Residuals: Min Q1 Med Q3
Max -1.9928118 -0.6586834 -0.1004301 0.6949714 2.0225381
Number of Observations: 60Number of Groups: 12
> lmer(root~fertilizer+(week|plant),data=dat)Linear mixed model fit by
> REML Formula: root ~ fertilizer + (week | plant) Data: dat AIC BIC
> logLik deviance REMLdev 174.4 187 -81.21 159.7 162.4Random
> effects: Groups Name Variance Std.Dev. Corr plant
> (Intercept) 4.1416e-18 2.0351e-09 week 8.7452e-01
> 9.3516e-01 0.000 Residual 2.2457e-01 4.7389e-01 Number of
> obs: 60, groups: plant, 12
Fixed effects: Estimate Std. Error t value(Intercept)
-0.1847 0.2024 -0.913fertilizercontrol -0.7612 0.2862 -2.660
Correlation of Fixed Effects: (Intr)frtlzrcntrl -0.707
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
