R help - Jul 2021 - ask for help about lme function

Dear R project,

I am a doctoral student in Zhejiang university in China, I am using lme function
in nlme package and learning the function by Package 'nlme' document. I
am writing this email for some help to build a lme model.

My goal was to include two non-nested random effects in the lme model. the
document described how to write the random effects while I found it difficult
for me to understand. My problem are as below:




In these model, site and year were considered as non nested effects. I want to
set the structure in lme model the same as lmer model(the 1st model below), and
I used the structure "random=list(site=~1,year=~1)"(the 2nd model
below) . According to the result, the  lme model was obviously wrong, for the R2
and AIC were different from that of lmer model. I want to know to get the same
result as lmer model, how should I set the random argument?

Below is the model and results in R,




################################################################1. lmer function
lmer<-lmer(data, y~x1+x2+x3+(1|site)+(1|year))             
r2(lmer)##58.8%?29.7%
r.squaredGLMM(lmer)##58.8%; 29.72%;AIC=462.4
###################################################################2. lme1
lme1<-lme(data, y~x1+x2+x3,random = list(site=~1,year=~1))              
r2(lme1)## NA(can't get the result)
r.squaredGLMM(lme1)##92.4%; 30.89%;AIC=533




I will be appreciated for your help.




Yours sincerely,

Juan Liu

Juan Liu

PhD candidate

College of Life Sciences, Zhejiang University

866 Yuhangtang Road, Hangzhou

Zhejiang 310058, P.R.China

21707095 at zju.edu.cn? liujuan_1994 at outlook.com



	[[alternative HTML version deleted]]

You might get better answers on the r-sig-ME list.

The lmer() function from lme4 handles crossed and non-nested random effects
quite seamlessly. I cannot comment on whether or not lme() can as well.

-- 
Kevin E. Thorpe
Head of Biostatistics,  Applied Health Research Centre (AHRC)
Li Ka Shing Knowledge Institute of St. Michael's
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.thorpe at utoronto.ca  Tel: 416.864.5776  Fax: 416.864.3016
> On Jul 20, 2021, at 10:32 AM, Juan Liu <21707095 at zju.edu.cn>
wrote:
> 
> EXTERNAL EMAIL:
> 
> Dear R project,
> 
> I am a doctoral student in Zhejiang university in China, I am using lme
function in nlme package and learning the function by Package 'nlme'
document. I am writing this email for some help to build a lme model.
> 
> My goal was to include two non-nested random effects in the lme model. the
document described how to write the random effects while I found it difficult
for me to understand. My problem are as below:
> 
> 
> 
> 
> In these model, site and year were considered as non nested effects. I want
to set the structure in lme model the same as lmer model(the 1st model below),
and I used the structure "random=list(site=~1,year=~1)"(the 2nd model
below) . According to the result, the  lme model was obviously wrong, for the R2
and AIC were different from that of lmer model. I want to know to get the same
result as lmer model, how should I set the random argument?
> 
> Below is the model and results in R,
> 
> 
> 
> 
> ################################################################1. lmer
function
> lmer<-lmer(data, y~x1+x2+x3+(1|site)+(1|year))
> r2(lmer)##58.8%?29.7%
> r.squaredGLMM(lmer)##58.8%; 29.72%;AIC=462.4
> ###################################################################2. lme1
> lme1<-lme(data, y~x1+x2+x3,random = list(site=~1,year=~1))
> r2(lme1)## NA(can't get the result)
> r.squaredGLMM(lme1)##92.4%; 30.89%;AIC=533
> 
> 
> 
> 
> I will be appreciated for your help.
> 
> 
> 
> 
> Yours sincerely,
> 
> Juan Liu
> 
> Juan Liu
> 
> PhD candidate
> 
> College of Life Sciences, Zhejiang University
> 
> 866 Yuhangtang Road, Hangzhou
> 
> Zhejiang 310058, P.R.China
> 
> 21707095 at zju.edu.cn? liujuan_1994 at outlook.com
> 
> 
> 
>        [[alternative HTML version deleted]]
> 
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