[R] Repeated measures
danbebber at forestecology.co.uk
Thu Oct 7 13:35:00 CEST 2004
I'm not sure I quite understand your question. Am I right in thinking that:
state = a binomial dependent variable
measure = a continuous predictor
If so, perhaps you could try using glmmPQL (Generalized Linear Mixed Models
fitted by Penalized Quasi-Likelihood) in library MASS.
The model would include random intercepts for each individual, have binomial
errors, and some kind of continuous autoregressive error structure (I
expect), and would look something like
If I've got the wrong end of the stick, my apologies.
Department of Plant Sciences
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Tel. 01865 275000
Date: Wed, 6 Oct 2004 08:07:38 -0400
From: Sean Davis <sdavis2 at mail.nih.gov>
Subject: [R] Repeated measures
To: r-help <r-help at stat.math.ethz.ch>
Message-ID: <5125203F-1790-11D9-97DA-000A95D7BA10 at mail.nih.gov>
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I have a data set in which I have 5000 repeated measures on 6 subjects
over time (varying intervals, but measurements for all individuals are
at the same times). There are two states, a "resting" state (the
majority of the time), and a perturbed state. I have a continuous
measurement at each time point for each of the individuals. I would
like to determine the "state" for each individual at each time point.
It looks to me like I should be able to do this with the "hidden"
command from the "repeated" package
(http://popgen0146uns50.unimaas.nl/~jlindsey/rcode.html), but I have
found it a bit confusing to get started. The distributions in the two
states are approximately normal with differences in centrality and
possibly variance (but I can start by assuming similar variances).
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