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...are two treatment replicates at each site even though there was only one exclosure at each site. I have analysed biomass for example already using ##this is the general linear model analysis, fitting a variation of the gamma distribution model3<-glm(Biomass~(Treatment+Time+Site)^3, data=bobB, family=quasi(link="log", variance="mu")) based upon initial data exploration and what the residuals were doing, that is the reason the residuals were spreading out was because I had a Gamma type error distribution and that model worked really well with the diagnostic plots. T...

...the same user several times. I.E. user "Mark" is logged into the server 2 times. I need to restrict him to logging in only once. Samba version 2.0.7 PID Username Machine Time logged in ------------------------------------------------------------------- 8703 bobb chinaberry Wed Nov 24 09:19:40 2004 21659 vadim vadim Tue Nov 30 08:07:12 2004 20949 mattm willow Mon Nov 29 13:00:27 2004 21642 rose cjs7 Tue Nov 30 07:28:39 2004 20810 paul cj...

Hello and thanks in advance I am running a glm in R the code is as follows with residual diagnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to...

This is my first rails program and I?m having trouble figuring out how to show rows on the page when there may not be rows in the database. There are 3 tables, employees, cost_codes and timesheet, I will simplify them when describing them later on. When an employee logs in, I would like to pull up their timesheet, which should consist of one row per cost code. So timesheet would look a

...39; Subject: GLM Repeated measures test of assumptions: e.g. test for sphericity e.g. Bartletts and Levenes homogenous variances Hello and thanks in advance I am running a glm in R the code is as follows with residual diagnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to...