Message-ID: <B9F402C0-CBD0-4939-87CB-8D3B4CF2478F@imperial.ac.uk>
Date: 2010-03-03T15:32:52Z
From: Federico Calboli
Subject: Conditional logistic regression vs lmer
In-Reply-To: <3D3B95AE-7C91-4C29-94A9-244B73BA8980@imperial.ac.uk>
Sorry to dig up an unexciting topic, but the number of random effects in my analysis is increasing so I would like to figure things out. I was trying to compare conditional logistic regression with logistic regression with random terms:
> I am doing a conditional logistic regression with clogit() of library survival, but I have a number of random factors I'd like to add to my model and I was thinking of lmer...
>
> clg.tigeR = clogit(c.c ~ tIgE.Resp + strata(match), data.ready)
>
> and all is good. I also have two more variables, both random which I'd like to use, but I am not 100% sure what's the way to go with lmer. I suspect I would need to specify a different intercept for each strata, but seems to baffle me at the moment. The code below might do what I want, but I have no idea if that's correct (i.e. does it match the clogit one + two more random effects?):
>
> lmer.tigeR = lmer(c.c ~ tIgE.Resp + (tIgE.Resp|match) + (1|Run) + (1|Box), family = binomial, data.ready)
>
> lmer.tigeR is computed without problems btw.
Most importantly, I utterly fail to see the conceptual difference between *nesting* in a logistic regression with random terms and *strata* in a conditional logistic regression, but that's probably just me.
Best,
F
--
Federico C. F. Calboli
Department of Epidemiology and Biostatistics
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG
Tel +44 (0)20 75941602 Fax +44 (0)20 75943193
f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com