Multinomial logist regression
Hi Steve,
Hi, I've been working up a dataset of soils and vegetation and I'd like to run a multinomial regression model with this data. ?The data includes six possible outcomes (vegtation types) and anywhere from 1 to 5 independent predictors (nutrient and hydrological properties). ?I've been looking at the mlogit package, globaltest (bioconductor) package, and glm modeling capabilities. Using the globaltest package I came up with a solution, but have some reservations. Which package and function is more commonly used for ecological investigations of this kind? How can I develop a plot illustrating the probabilities of each of the six response vegetation types for a given concentration of nutrients (the independent predictors) ? Eventually, I will add several predictors to this model. Is there a method that I can use that will allow me to use multiple predictors and multiple responses ? If anyone really wants to see the code I'm using, I'll have to get it from my office tomorrow. Thanks Steve
I am not sure if I am on the right track here but you might check out Frank Harrell rms package. It sounds as if the Proportional Odds model may work for you. There is a paper by Guisan and Harrell that may be of interest. Also Franks Regression Modeling Strategies book has some nice examples for plotting such models. I am not sure how often these methods are used in ecology though. Guisan, A., and F. E. Harrell. 2000. Ordinal response regression models in ecology. JOURNAL OF VEGETATION SCIENCE 11:617-626. Hope this helps, Michael
Michael Denslow I.W. Carpenter Jr. Herbarium [BOON] Department of Biology Appalachian State University Boone, North Carolina U.S.A. -- AND -- Communications Manager Southeast Regional Network of Expertise and Collections sernec.org 36.214177, -81.681480 +/- 3103 meters