Hi all, I have a large set of data that looks something like this, although this data frame is much smaller and includes made up numbers to make my question easier.
> x.df <- data.frame(Region = c("A", "A", "A", "A", "A", "B", "B", "B", "B", > "B", "B", "C", "C", "C", "C"), Group_ID = c(1:15), No_Offspring = c(3, 0, 4, > 2, 1, 0, 3, 4, 3, 2, 2, 5, 4, 1, 3), M_Offspring = c(2, 0, 2, 1, 0, 0, 1, 1, > 2, 0, 1, 3, 2, 1, 1), F_Offspring = c(1, 0, 2, 1, 1, 0, 2, 3, 1, 2, 1, 2, 2, > 0, 2), No_Helpers = c(5, 0, 2, 1, 0, 1, 3, 4, 2, 3, 2, 3, 4, 0, 0)) > x.df Region Group_ID No_Offspring M_Offspring F_Offspring No_Helpers 1 A 1 3 2 1 5 2 A 2 0 0 0 0 3 A 3 4 2 2 2 4 A 4 2 1 1 1 5 A 5 1 0 1 0 6 B 6 0 0 0 1 7 B 7 3 1 2 3 8 B 8 4 1 3 4 9 B 9 3 2 1 2 10 B 10 2 0 2 3 11 B 11 2 1 1 2 12 C 12 5 3 2 3 13 C 13 4 2 2 4 14 C 14 1 1 0 0 15 C 15 3 1 2 0 I have been using GLMs to determine if the number of helpers (No_Helpers) has an effect on the sex ratio of the offspring. Here's the GLM I have been using: > prop.male <- x.df$M_Offspring/x.df$No_Offspring > glm = glm(prop.male~No_Helpers,binomial,data=x.df) However, now I'd like to fit a model with region-specific regressions and see if this has more support than the model without region-specificity. So, I'd like one model that generates a regression for each region (A, B, & C). I've tried treating No_Helpers and Region as covariates: > glm2 = glm(prop.male~No_Helpers+Region-1,binomial,data=x.df) which includes region-specificity in the intercepts, but not the entire regression, and as interaction terms: > glm3 = glm(prop.male~No_Helpers*Region-1,binomial,data=x.df) which also does not give me an intercept and slope for each region. I'm not sure how else to adjust the formula, or if the adjustment should be somewhere else in the GLM call. Thanks in advance for your help. ______________________________________________ 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.