R help - Oct 2010 - Question about lme (mixed effects regression)

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

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
>
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> and provide commented, minimal, self-contained, reproducible code.
>


-- 
Bert Gunter
Genentech Nonclinical Biostatistics