GEE and AIC
See Pan (2001). Akaike's information criterion in generalized estimating equations. Biometrics 57: 120-125. See also the book by Hardin and Hilbe 2003 for examples and applications. ?The only reason to jump to gee is if your dependent variable is not Gaussian (but is an exponential family, e.g. binomial, Poisson, etc.), and you have several covariates, some of which may be continuous. You should be careful with your model of evolution if your dependent variable is non-Gaussian. Brownian motion cannot apply to discrete variables. Instead, a discrete-state, continuous time Markov model might be more appropriate, in which case you can't directly use the shared branch-lengths of the phylogeny as estimates of phylogenetic covariance. See Martins and Hansen 1997 Phylogenies and the comparative method: a general ?approach to incorporating phylogenetic information into the analysis of interspecific ?data. American Naturalist 149:646?667. Erratum 153:448. Tony Ives and Ted Garland have submitted a manuscript on this topic, but you will have to contact them for further info. The sample size has little to do with the issue, although fitting gee models with small sample sizes can be extremely difficult. There are also formidable problems with bias in the parameter estimates. I've cc'ed this to r-sig-phylo, which is probably a better forum for discussing comparative analyses. Cheers, Simon.
Thu, 2008-05-29 at 15:50 -0700, BriAnne Addison wrote:
This is tangential to the previous string. Has anyone calculated (pseudo)AIC values for generalized estimation equations in the GEE package (or related packages)? I wish to compare among several models where the data are not phylogenetically independent. I plan to use GEE to account for my phylogeny, rather than conventional contrast values, because I have a relatively small sample size and a variety of continuous and multilevel discrete factors. The statistical problem is analogous to data which is spatially autocorrelated. Thoughts? Thanks, BriAnne ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BriAnne Addison Ecology, Evolution and Systematics Biology Department University of Missouri - St Louis brianne.addison at umsl.edu
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Simon Blomberg, BSc (Hons), PhD, MAppStat. Lecturer and Consultant Statistician Faculty of Biological and Chemical Sciences The University of Queensland St. Lucia Queensland 4072 Australia Room 320 Goddard Building (8) T: +61 7 3365 2506 http://www.uq.edu.au/~uqsblomb email: S.Blomberg1_at_uq.edu.au Policies: 1. I will NOT analyse your data for you. 2. Your deadline is your problem. 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.