[R-sig-ME] generalized linear mixed-effects model and lmer, lme

[Qinglin Wu]

Dear list,

I am the new R user and just start last Friday.  I am fitting the generalized linear mixed-effects model and going to use "glmer" function.  I don’t understand the following two examples in the glmer function documentation:

Example 1:  lmer(Reaction ~ Days + (Days | Subject), sleepstudy))
Example 2:  lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy))

In example 1,  i can write the model as:  
reaction = a_0 + a_1*days + b_0 + b1*days. 
The fixed effecta are a_0 + a_1*days, the random effects are b_0 + b1*days.

How can you explain example 2?  Can I write the model as:  
reaction = a_0 + a_1*days +  b_0 + c1*days.  

these two have the same fixed effect.  What is the random effects in example 2?   Is it b_0 + c1*days?  Or one random effect is b_0 and another one is c1*days?  If I use "lme" function, how can I write it in the “random” argument.     

Their results are totally different.


Another question, I tried the function “lme”.  I think it should have the same result with the function "lmer".  But it didn’t.

I tried the following models:   
lme(distance ~ age + Sex, data = Orthodont, random = ~ age+Sex)
lmer(distance~age+Sex+(age+Sex|Subject),Orthodont)
lmer(distance~age+Sex+((age+Sex)|Subject),Orthodont)
  
They have the almost same results except “Corr” in the random effects.  

I don’t know how the two functions work in the R.  I checked the functions in the package. We can not look them.   Does anybody know there are some other places so that I can look the source code and then I know how they work.  

Any help would be appreciated.


Cynthia Wu