Conference Presentations

August 15, 2012
By

(This article was first published on Daniel Hocking, Ecologist » Blog, and kindly contributed to R-bloggers)

I recently gave a talk at the Ecological Society of America (ESA) annual meeting in Portland, OR and a poster presentation at the World Congress of Herpetology meeting in Vancouver, BC, Canada. Both presentations were comparing generalized linear mixed models (GLMM) and generalized estimating equations (GEE) for analyzing repeated count data. I advocate for using GEE over the more common GLMM to analyze longitudinal count (or binomial) data when the specific subjects (sites as random effects) are not of special interest. The overall confidence intervals are much smaller in the GEE models and the coefficient estimates are averaged over all subjects (sites). This means the interpretation of coefficients is the log change in Y for each 1 unit change in X on average (averaged across subjects). Below you can see my two presentations for more details.

WCH2012-poster-Hocking

ESA–ppt-Presentation-2012-Hocking


Filed under: GEE, GLMM, Modeling Tagged: Analysis, ESA, GEE, generalized estimating equations, generalized linear mixed models, GLMM, JMIH, modeling, poster, powerpoint, presentation, regression, WCH

To leave a comment for the author, please follow the link and comment on his blog: Daniel Hocking, Ecologist » Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , , , , , , , , , , ,

Comments are closed.