[R] Model building using lmer

[ONKELINX, Thierry]

Dear Luciano,

The "1" in (1|NestID) indicates only a random intercept. Note that in
most models in R, a "1" on the righthandside of the formula indicates
the intercept, "-1" or "0" indicates no intercept. ~X, which is
equivalent to ~X + 1, indicates a slope along X and an intercept. Hence
a random slope and intercept is write as (X|NestID). If you only want
the random slope then write (X + 0|Nest).

Note that (X|NestID) implies that the random slope and the random
intercept can be correlated. If you need them to be independent you will
have to write (X + 0|NestID) + (1|NestID).

HTH,

Thierry

PS Next time try to send questions about lmer to the R-sig-mixed-models
mailinglist.



------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-help-bounces op r-project.org [mailto:r-help-bounces op r-project.org]
Namens Luciano La Sala
Verzonden: woensdag 17 december 2008 15:47
Aan: r help
Onderwerp: [R] Model building using lmer

Dear R-experts,
Quite new to R on this end, but learning fast (I hope). 

I am running version 2.7.1 on Windows Vista. I have small dataset
which consists of: 

# NestID: nest indicator for each chicken. Siblings sharing the same
nest have the same nest indicator. 

# Chick: chick indicator consisting of a unique ID for each single
chick. 

# Year: 1, 2.

# ClutchSize: 1-, 2- , 3-eggs.  

# HO: hatching order within each clutch (1, 2, 3 [first, second and
third-hatched chick]).

# SibComp: sibling competence: present/ absent (0, 1)

# Death2: death at two days post-hatch (0, 1)

# Death10: death at ten days post-hatch (0, 1)

So a subset of my dataset looks something like this:


NestID Chick Year ClutchSize HO Hatching SibComp Death2 Death10
1          1    1          1  1        1       1      1       1
2          2    1          1  1        1       1      0       0
3          3    1          1  1        0       0      0       0
4          4    1          1  1        1       0      1       0
4          5    1          2  2        0       1      0       1
5          6    1          2  1        1       0      0       0
5          7    1          2  2        0       0      0       0
6          8    2          3  1        1       1      0       0
6          9    2          3  2        1       0      1       0
6          10   2          3  3        0       1      0       0
7          11   2          3  1        0       0      0       1   
7          11   2          3  2        0       0      0       0 
7          11   2          3  3        1       1      1       1        
............

In order to account for lack of independence at the nest level (many
chicks are siblings), I'd like to run a GLMM with random slopes and
intercepts for nests.

Using lmer, my model for survival at 10 days, for example, would read as
follows (or not!): 

> model <- lmer(Death10 ~ HO + ClutchSize + SibComp + Year + (1|NestID),
family=binomial, 1)

> summary(model)

>From what I understand, the model above includes only random intercepts
for NestID. So at this point my question is how do I make this model
into one which includes both random intercepts and slopes for NestID? 

Look forward to receiving your input. Thank you all for your time! 

Luciano

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