Hi R- listeners, I should add that I would like also to compare my field data to an index model. The index was created by using the following script:
devel.index <- function(values, weights=c(1, 2, 3, 4, 5, 6)) { foo <- values*weights return(apply(foo, 1, sum) / apply(values, 1, sum)) } Background: Surveyed turtle egg embryos have been categorized into 6 stages of development in the field. The stages in the field data are named ST0, ST1, ST2, ST3, ST4, Shells. from the data = data.to.analyze. Q? 1. What is the best way to analyze the field data on embryonic development of 6 stages? 2. Doing this while considering, testing the variables: Veg, HTL, Aeventexhumed, Sector, Rayos, TotalEggs? 3. And then compare the results to a development index. The goal is to determine hatching success in various areas of the beach. And try to create a development index of these microenvironments. Seasonality would play a key role. Is this possible? Many thanks! Saludos, Jean -- View this message in context: http://r.789695.n4.nabble.com/How-do-I-compare-47-GLM-models-with-1-to-5-interactions-and-unique-combinations-tp4326407p4329909.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.