R help - Sep 2016 - Cross-classified multilevel binary logistic regression model with random effects at level 2

Hello

I am not a seasoned R user and am therefore keen to identify a book chapter that
can provide structured advice on setting up the type of model I am interested in
using R. I would like to run a cross-classified multilevel binary logistic
regression model. The model contains two level 2 random effects variables. These
variables are crossed to form a cross-classified design. The model has subjects
at level one and these subjects are nested within each of the two level two
variables. I understand that the R package lme4 may be suitable for running my
model and that there are several published books on running mixed models in R.
If a list member is able to kindly recommend whether one of these books is
particularly helpful in helping less experienced R users fully understand how to
use this (or an alternative) program specifically for the model I have outlined
above, I would be most grateful for recommendations.

Thank you so much

Best wishes

Margaret

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> On Sep 14, 2016, at 6:05 AM, MACDOUGALL Margaret <Margaret.MacDougall at
ed.ac.uk> wrote:
> 
> Hello
> 
> I am not a seasoned R user and am therefore keen to identify a book chapter
that can provide structured advice on setting up the type of model I am
interested in using R. I would like to run a cross-classified multilevel binary
logistic regression model. The model contains two level 2 random effects
variables. These variables are crossed to form a cross-classified design. The
model has subjects at level one and these subjects are nested within each of the
two level two variables. I understand that the R package lme4 may be suitable
for running my model and that there are several published books on running mixed
models in R. If a list member is able to kindly recommend whether one of these
books is particularly helpful in helping less experienced R users fully
understand how to use this (or an alternative) program specifically for the
model I have outlined above, I would be most grateful for recommendations.
You would get the widest and most knowledgeable audience for this question at
the MixedModels mailing list.

https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
-- 


David Winsemius
Alameda, CA, USA

Thank you for this valued advice, David, in response to which I have sent a very
similar message to the list you recommend.  I would also welcome suggestions
from members of the r-help at r-project list, where appropriate.

Best wishes

Margaret






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Scotland, with registration number SC005336.


-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net] 
Sent: 14 September 2016 16:17
To: MACDOUGALL Margaret <Margaret.MacDougall at ed.ac.uk>
Cc: r-help at r-project.org
Subject: Re: [R] Cross-classified multilevel binary logistic regression model
with random effects at level 2

> On Sep 14, 2016, at 6:05 AM, MACDOUGALL Margaret <Margaret.MacDougall at
ed.ac.uk> wrote:
> 
> Hello
> 
> I am not a seasoned R user and am therefore keen to identify a book chapter
that can provide structured advice on setting up the type of model I am
interested in using R. I would like to run a cross-classified multilevel binary
logistic regression model. The model contains two level 2 random effects
variables. These variables are crossed to form a cross-classified design. The
model has subjects at level one and these subjects are nested within each of the
two level two variables. I understand that the R package lme4 may be suitable
for running my model and that there are several published books on running mixed
models in R. If a list member is able to kindly recommend whether one of these
books is particularly helpful in helping less experienced R users fully
understand how to use this (or an alternative) program specifically for the
model I have outlined above, I would be most grateful for recommendations.
You would get the widest and most knowledgeable audience for this question at
the MixedModels mailing list.

https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
-- 


David Winsemius
Alameda, CA, USA