Hello r-help, I try to fit birds counts over years using glm. I have done (with Estate and year as factors): Model1 <- glm(Females~Estate+Year+offset = log(area)), family quasipoisson(link = log), na.action = "na.exclude") After I have calculated the prediction using: Pred1 <- predict(Model1, type = "response", na.action = "na.exclude") My question is: How can I obtain predictions for Females in each year that are standardized by averaging over the levels of Estate? I have been advised to use log(area) as an offset because we are actually interested in density of birds but would appreciate any good comparisons between offset and weight. Thanks in advance for any help you can give. Hugues SANTIN-JANIN hugues_sj@yahoo.fr "Game Conservancy Trust" **Win some fantastic prizes in our 2005 prize draw. Visit www.gct.org.uk, click on the membership menu and choose 2005 Prize Draw and purchase your draw tickets.** E-mail Disclaimer This communication from Hugues Santin-Janin contains information which is CONFIDENTIAL and may also be privileged. It is for the exclusive use of the addressee. If you are not the addressee please note that any distribution, copying or use of this communication or the information in it is prohibited. If you have received this communication in error, please telephone us immediately to arrange for its return. [[alternative HTML version deleted]]
Hello r-help, I try to fit birds counts over years using glm. I have done (with Estate and year as factors): Model1 <- glm(Females~Estate+Year+offset = log(area)), family quasipoisson(link = log), na.action = "na.exclude") After I have calculated the prediction using: Pred1 <- predict(Model1, type = "response", na.action = "na.exclude") My question is: How can I obtain predictions for Females in each year that are standardized by averaging over the levels of Estate? I have been advised to use log(area) as an offset because we are actually interested in density of birds but would appreciate any good comparisons between offset and weight. Thanks in advance for any help you can give. Hugues SANTIN-JANIN hugues_sj@yahoo.fr "Game Conservancy Trust" --------------------------------- [[alternative HTML version deleted]]
Hugues Santin-Janin <hsantin-janin <at> gct.org.uk> writes:> I try to fit birds counts over years using glm. I have done (with Estate > and year as factors): > > Model1 <- glm(Females~Estate+Year+offset = log(area)), family > quasipoisson(link = log), na.action = "na.exclude")..> Pred1 <- predict(Model1, type = "response", na.action = "na.exclude") > > My question is: How can I obtain predictions for Females in each year > that are standardized by averaging over the levels of Estate?You should use the newdata argument in predict.glm to construct the "should-be" data set. The example on the page ?predict.glm creates budworm-data on the fly, but it's probably easier to understand if you create a separate data frame myfemales first, the do predict(Model1, newdata=myfemales,..) in a separate step. Dieter Menne