This might be a question for the programmers, but I thought I would ask here first. Im comparing browsing pressure on plants between sites. Ive a value to indicate Browsing Pressure and count data of trees that have been damaged between locations. Ive been using Crawleys R example (page 574) regarding sex ratios and my … Read more
I have two logistic regression models in R made with glm(). They both use the same variables, but were made using different subsets of a matrix. Is there an easy way to get an average model which gives the means of the coefficients and then use this with the predict() function? [ sorry if this … Read more
I'm trying to fit models that predict probabilities: $h(X,B) rightarrow (0,1)$ It struck me that for for a great many cases logistic regression seems like a bad link function, I expect an S-curve, but I also expect bounds on the predicted probability to be much larger than 0, and much less than 1. For example, … Read more
For a generalized linear model, the residual deviance is often described as having asymptotically a chi-squared null distribution. I read that it's the case, for example http://thestatsgeek.com/2014/04/26/deviance-goodness-of-fit-test-for-poisson-regression/ but I can't figure out why. Can you help with an explanation? Best Answer Your original question was rather cryptic, but I will assume that you are referring … Read more
I'm trying to replicate a model fitted in SAS in R but the fit I'm getting gives me slightly different coefficients and standard errors. Data: testdata <- data.frame(matrix(c("f","Test", 1.75, 16, 0, 16, 0, 1, 1, "m", "Test", 1.75, 15, 1, 16, 6.25, 1, 0, "f", "Test", 2.75, 4, 12, 16, 75, 1, 1, "m", "Test", … Read more
I'm trying to replicate a model fitted in SAS in R but the fit I'm getting gives me slightly different coefficients and standard errors. Data: testdata <- data.frame(matrix(c("f","Test", 1.75, 16, 0, 16, 0, 1, 1, "m", "Test", 1.75, 15, 1, 16, 6.25, 1, 0, "f", "Test", 2.75, 4, 12, 16, 75, 1, 1, "m", "Test", … Read more
I was just wondering if Poisson regression has an error term? Can a Poisson regression have random effects and an error term? I am confused about this point. In logistic regression, there is no error term because your outcome variable is binary. Is that the only glm model that doesn't have a residual term? Best … Read more
I was just wondering if Poisson regression has an error term? Can a Poisson regression have random effects and an error term? I am confused about this point. In logistic regression, there is no error term because your outcome variable is binary. Is that the only glm model that doesn't have a residual term? Best … Read more
Why linear regression and Generalized Model have inconsistent assumptions? In linear regression, we assume residual comes form Gaussian In other regression (logistic regression, poison regression), we assume response comes form some distribution (binomial, poission etc.). Why sometimes assume residual and other time assume on response? Is is because we want to derive different properties? EDIT: … Read more
I have a quick question about reporting simple main effects. I am running a two-way mixed ANOVA and the interaction effect was not significant. I understand that if you have no significant interaction effect, you should not carry out a test of simple main effects and instead just interpret the main effects. I really don't … Read more