[R] Model building using lmer
ONKELINX, Thierry
Thierry.ONKELINX at inbo.be
Wed Dec 17 16:51:16 CET 2008
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
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say what the experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
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ensure that a reasonable answer can be extracted from a given body of
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-----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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