From: Luis Cayuela <luis.cayuela_at_uah.es>

Date: Wed, 21 May 2008 14:12:28 +0200

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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. Received on Wed 21 May 2008 - 12:19:28 GMT

Date: Wed, 21 May 2008 14:12:28 +0200

Thanks for the help provided to fit the model. I still have two questions:

- What is the syntax for nested fixed and random factors. I have tried using the %in% operator but it does not work. The model I want to fit would be as follow:

lmer 1 <- lmer(Growing ~ Seed + Species%in%Seed + Treatment + (1|Block%in%Treatment), data)

2) Seed, Species and Treatment are intra-subject factors. This means that an ANOVA of repeated measure should apply here. How should this be specified in the model? Or should I assume that this is incorporated by specifying the Block as a random factor?

All the best,

Luis

Luis Cayuela

Departamento de Ecología

Universidad de Alcalá

Crta. de Barcelona km. 33,600

E-28871 Alcalá de Henares

Madrid

España

Tlf: (+0034) 918856407

Fax: (+0034) 918854929

----- Original Message -----

From: "Douglas Bates" <bates_at_stat.wisc.edu>
To: "Luis Cayuela" <luis.cayuela_at_uah.es>
Cc: <r-help_at_r-project.org>

Sent: Thursday, May 15, 2008 5:22 PM

Subject: Re: [R] mixed effects models with nested factors

On Thu, May 15, 2008 at 9:22 AM, Luis Cayuela <luis.cayuela_at_uah.es> wrote:

*> Hi everybody,
*

> I am trying to fit a model with the lmer function for mixed effects. I

*> have an experimental design consisting of 5 field plots. Each plot is
**> divided in 12 subplots where the influence of three factors on the growing
**> of tree seedlings is tested: (1) seed (1 = presence; 0 = absence); (2)
**> seedling species (oak holm vs. pine); (3) treatment (three different
**> treatments). In each of these subplots we planted 13 seedlings. Therefore
**> I would have a model with three fixed factors and one random factor (a
**> block?). If I´m not wrong the model would be as follows:
*

> model2 <- lmer(Growing ~ Seed + Species + Treatment +(Seed + Species +

*> Treatment|Block), data)
*

That's unlikely. This specification would fit 5 fixed effects parameters and 5, possibly correlated, random effects for each level of the Block factor. This would require estimating a total of 15 variance-covariance parameters for the random effects from the 5 blocks.

Can you indicate how many random effects you expect to obtain and how many variance-covariance parameters would be involved? For example, a model with a simple random effect would be expressed as

lmer(Growing ~ Seed + Species + Treatment + (1|Block), data)

and would involve estimating the 5 fixed effects and one variance for
the random effects.

> My first question is: if the three fixed factors occur within-subjects

*> (considering the plot as a subject), is the model correctly defined
**> (assuming no interactions)? Should I specify the model in some other way?
**>
**>
**>
**> I second problem I had is that the factors are not crossed because some of
**> the seedling died during the experiment. This means that some factors are
**> nested. Specifically Species is nested within Seed and Block would be
**> nested within Treatment. I have tried to use the %in% specification for
**> nested designs but it does not work.
**>
**>
**>
**> model2 <- lmer(Growing ~ Seed + Species%in%Seed + Treatment +(Seed +
**> Species + Treatment|Block%in%Treatment), data)
**>
**>
**>
**> I get the following error:
**>
**>
**>
**> Error en lmer(Growing ~ Seed + Species %in% Seed + Treatment + : ..
**>
**> Leading minor of order 5 in downdated X'X is not positive definite
**>
**>
**>
**> I would appreciate some help to fit this model.
**>
**>
**> Thanks to everybody,
**>
**> Luis
*

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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. Received on Wed 21 May 2008 - 12:19:28 GMT

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