[R-sig-ME] glmer random effects structure: a case

[John Morrongiello]

Hi Simone
Maybe  technique behavioural ecologists call 'within subject centring' might be of use? This allows you to decompose a mean response (var2 coefficient) into its within and among individual components. See the references below for further details

van de Pol, M. V., and J. Wright. 2009. A simple method for distinguishing within- versus between-subject effects using mixed models. Animal Behaviour 77:753-758.
Dingemanse, N. J., and N. A. Dochtermann. 2013. Quantifying individual variation in behaviour: mixed-effect modelling approaches. Journal of Animal Ecology 82:39-54.

Cheers
John
--
Dr. John R. Morrongiello
School of BioSciences
University of Melbourne
Victoria 3010, Australia
T: +61 3 8344 8929
M: +61 403 338 554
E: john.morrongiello at unimelb.edu.au
W: morrongiellolab.com

Message: 1
Date: Sat, 14 Nov 2015 17:48:46 +0100
From: Simone <miseno77 at hotmail.com>
Cc: "r-sig-mixed-models at r-project.org"
	<r-sig-mixed-models at r-project.org>
Subject: [R-sig-ME] glmer random effects structure: a case
Message-ID: <DUB122-W23B9A81CF0199D75E296E6DC100 at phx.gbl>
Content-Type: text/plain; charset="UTF-8"


Hi all,
I have a simple (but not that simple to me) question on how to specify the random structure in R.A binary response variable (Var1) has been measured from a number of individuals (IND) that have been susceptible of being captured over a number of dates (DATE). I suspect that Var1 might depend either on its sex (SEX), or age (AGE) or Var2 which is a continuous variable measured from each individual every time it is captured. Since Var2 is a measure of the quality of each individual, it is likely that some individuals will tend to have greater values of Var2 than others during the entire study period.Note that some individuals have been captured only one time, other two, other three and so on (very unbalanced). For each date an individual can be captured only one time.So, I have two groups: IND and DATE. I would think this is a two-level model with IND nested to DATE so that:
model1 <- glmer(Var1 ~ SEX + AGE + Var2 + (1|DATE/IND), family = binomial, data = mydata) Does it make sense? I think i am not taking into account the fact that the mean of Var2 may be different among individuals but I don't know how to do that.I would really appreciate an answer to this question that I am sure would help me a lot to understand better how mixed models work.
 		 	   		  
	[[alternative HTML version deleted]]