Hello all,
In a previous posting regarding glmm.admb it is stated that glmm.admb
can handle 2 nested random effects. I can only fit a single random
term at the moment, and wondered if anyone could provide me with some
information on how to specify a model with 2 (nested or
out how to do 2-level nesting, and include that in future
releases.
hans
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Jarrod Hadfield
Sent: Wednesday, February 08, 2006 2:26 PM
To: r-help@stat.math.ethz.ch
Subject: [R] nested random effects
Hello
For an unbalanced longitudinal data set with subjects nested within
family as the random effect (random= ~1 | FAMILY/ID)-- I am unclear as to
why the subject within family random coefficient is not zero when there is
only one person in a family with only one data point.
Thanks
Dede
Hi
I am struggling with nested random effects and hope someone can help.
I have individuals (ID) who are nested within families (FAM). I want to
model an outcome variable, and take account of the intercorrelation of
individuals within each family.
I think this amounts to two random
On Wed, 2005-03-23 at 11:58 -0500, Shaw, Philip (NIH/NIMH) wrote:
Hi
I am struggling with nested random effects and hope someone can help.
I have individuals (ID) who are nested within families (FAM). I want to
model an outcome variable, and take account of the intercorrelation of
An interaction random effect/fixed effect is noted as
random ~1|random/fixed
in your case random =~1|ID/FAM (but I don't uderstand why indiviuals
withing families are fixed and and families are random, but there you
go).
1. Fixed effects cannot be nested within random effects.
2.
It should be random=~1|FAM/ID indicating individuals are nested within
families.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Federico Calboli
Sent: Wednesday, March 23, 2005 12:34 PM
To: Shaw, Philip (NIH/NIMH)
Cc: r-help
Subject: Re: [R] nested
On Wed, 2005-03-23 at 10:04 -0800, Berton Gunter wrote:
An interaction random effect/fixed effect is noted as
random ~1|random/fixed
in your case random =~1|ID/FAM (but I don't uderstand why indiviuals
withing families are fixed and and families are random, but there you
go).
I should have added that if you have only one Y observation per ID (within
family), then the ID variance component is residual error and the model
becomes (without any covariates)
Y~1, rand=~1|FAM
-- Bert
On Wed, 2005-03-23 at 11:58 -0500, Shaw, Philip (NIH/NIMH) wrote:
Hi
I am
