[R] Question about lme (mixed effects regression)

[Dimitri Liakhovitski]

Yes, sorry for the confusion. Maybe I should have used a different term.
So, I guess, I was right - it gives only the random effects that I
have to add to the fixed effects.
And there is no way to get it done by R (not that I can't do it myself)?
Dimitri


On Mon, Oct 18, 2010 at 6:24 PM, Bert Gunter <gunter.berton at gene.com> wrote:
> Oh -- I get your question (I think). Not the total, just the random
> effects. You have to add them to the fixed effects.
>
> See e.g. p. 39 of Bates and Pinheiro.
>
> -- Bert
>
> On Mon, Oct 18, 2010 at 3:00 PM, Dimitri Liakhovitski
> <dimitri.liakhovitski at gmail.com> wrote:
>> Thank you very much, but not I am not sure now - does ranef(fm1) give
>> the (total) slope and
>> intercept values directly for each group or not?
>> Thanks a lot for clarifying - because I might well have been wrong.
>> Dimitri
>>
>> On Mon, Oct 18, 2010 at 5:57 PM, Bert Gunter <gunter.berton at gene.com> wrote:
>>> Dmitri:
>>>
>>> Not quite sure what you mean by easier ... fixef() and ranef() will
>>> both give coefficients which can be easily manipulated to produce the
>>> results for all subjects.
>>>
>>> However, note that there are numerous built-in lme
>>> functions(especially for graphics) that do this internally to produce,
>>> e.g. graphs of coefficient shrinkage. So if this is the sort of thing
>>> you want to do with the BLUPS, you may not need to do it manually.
>>>
>>> HTH.
>>>
>>> Cheers,
>>> Bert
>>>
>>> On Mon, Oct 18, 2010 at 2:15 PM, Dimitri Liakhovitski
>>> <dimitri.liakhovitski at gmail.com> wrote:
>>>> Hello!
>>>>
>>>> If I run this example:
>>>>
>>>> library(nlme)
>>>> fm1 <- lme(distance ~ age+Sex, Orthodont, random = ~ age + Sex| Subject)
>>>> If I run:
>>>> summary(fm1)
>>>> then I can see the fixed effects for age and sex (17.7 for intercept,
>>>> 0.66 for age, and -1.66 for SexFemale)
>>>>
>>>> If I run:
>>>> ranef(fm1)
>>>> Then it looks like it's producing the random effects for each subgroup
>>>> (in this example - each subject). For example, for MO1 it's:
>>>> 1.25 for intercept, 0.106 for age, and -1.52 for SexFemale.
>>>>
>>>> So, in order to get the the total effects, i.e., the regression
>>>> equation, for each subgroup (Subject) I need to do this:
>>>> For example, for Subject MO1:
>>>> y(M01) = (17.71+1.25)+(0.66+0.106)*Age+(-1.66-1.52)*SexFemale = 18.96
>>>> + 0.766*Age -3.18*SexFemale
>>>>
>>>> Question: Is there an easier way to get such an equation for each
>>>> level of Subject?
>>>>
>>>> Thank you very much!
>>>>
>>>> --
>>>> Dimitri Liakhovitski
>>>> Ninah Consulting
>>>> www.ninah.com
>>>>
>>>> ______________________________________________
>>>> R-help at 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.
>>>>
>>>
>>>
>>>
>>> --
>>> Bert Gunter
>>> Genentech Nonclinical Biostatistics
>>>
>>
>>
>>
>> --
>> Dimitri Liakhovitski
>> Ninah Consulting
>> www.ninah.com
>>
>
>
>
> --
> Bert Gunter
> Genentech Nonclinical Biostatistics
>



-- 
Dimitri Liakhovitski
Ninah Consulting
www.ninah.com