search for: mserror

Hi there, I am trying to run LSD.test(model) I used the following commands: attach(model) m1<- glm(ttl.m ~ site+year, family=quasipoisson, data= model) df<-df.residual(m1) MSerror<-deviance(m1)/df The following command did not work: comparison<- LSD.test (ttl.m, site+year, df, MSerror, alpha = 0.05, group=FALSE) I get an error message: Error: could not find function "LSD.test" Do I need to download a special package for that? Any idea which one? or how to...

...treatment was significant. I would like compare treatment means using Tukey. I can't extract the mean square to apply HSD.test to use in agricolae package. anava = aov(ganhos ~ Blocos + Trat*Supl + Error(Blocos/Trat)) names(anava) summary(anava) require(agricolae) HSD.test(ganhos, Trat, df, MSerror, alpha = 0.05) Thanks -------------------------------------- Silvano Cesar da Costa Departamento de Estat?stica Universidade Estadual de Londrina Fone: 3371-4346

...r 6213 Total 6228 Hasta ahora todo marcha bien, pero cuando intento hacer las comparaciones multiples con LSD obtengo un error. Lo declare de la siguiente forma: Anavar<-aov(Resp~A*B*C,data=Resultado) Comparacion1 <- LSD.test(ANAVAR,"A*B*C",DFerror=6213,MSerror=0.01619,p.adj="bonferroni",group=T) Comentaros tambien que declare p.adj="bonferroni" pues los datos son desbalanceados. Agradezco cualquier sugerencia que podais dar Saludos!! [[alternative HTML version deleted]]

...toniB 2.60 136 carletoniB 2.40 137 carletoniB 2.60 145 schmidlyi 2.50 146 schmidlyi 2.70 147 schmidlyi 2.70 161 simulus 2.40 162 simulus 2.20 163 simulus 2.30 This is condensed. My data is called dat. The help for duncan.test shows the argument like this: duncan.test(y, trt, DFerror, MSerror, alpha = 0.05, group=TRUE, main = NULL) When I try to run it as duncan.test(aov, dat, 6, .297, alpha=.05, group=TRUE, main=NULL) it gives me an error message that I have differing rows, 0 and 163. 163 is the correct number, where is it getting the 0 from? Thank you, Amanda Jones

Hello list, I wish to perform a randomization test on the F-statistics of a 2 way ANOVA but have not been able to find out how to do so - is there a package / function that can perform this that I am unaware of? FactorA has 6 levels (0,1,2,3,4,5) whereas FactorB has 3 (1,2,3). A sample: Resp. FactorA FactorB 2 0 2 3 1 2 1 2 2 0 3 2 0 4 2 0 5 2 4 0 1 6 1 1 1 2 1 0 3 1 1 4 1 0 5 1 2 0 2 3 1 2 1

Dear all, I am trying to repeat an example from Sokal and Rohlfs "Biometry" -- Box 11.4, example of a randomized-complete-blocks experiment. The data is fairly simple: series genotype weight 1 pp 0.958 1 pb 0.985 1 bb 0.925 2 pp 0.971 2 pb 1.051 2 bb 0.952 3 pp 0.927 3 pb 0.891 3 bb 0.892 4