search for: mca2

Dear R-users, My question is how to get right F tests for random effects in random effect models (I hope this question has not been answered too many times yet - I didn't find an answer in rhelp archives). My data are in mca2 (enc.) : names(mca2) [1] "Lignee" "Pollinisateur" "Rendement" dim(mca2) [1] 100 3 replications(Rendement ~ Lignee * Pollinisateur, data = mca2) Lignee Pollinisateur Lignee:Pollinisateur 20 10...

Dear R-users, Sorry for reposting. I put it in another way : I want to test random effects in this random effect model : Rendement ~ Pollinisateur (random) + Lignee (random) + Pollinisateur:Lignee (random) Of course : summary(aov(Rendement ~ Pollinisateur * Lignee, data = mca2)) gives wrong tests for random effects. But : summary(aov1 <- aov(Rendement ~ Error(Pollinisateur * Lignee), data = mca2)) gives no test at all, and I have to do it with mean squares lying in summary(aov1). With "lme4" package (I did'nt succeed in writing a working formula with l...

bonjour, Je voudrais faire une analyse des correspondances multiples avec R. avec les repr?sentation graphiques correspondantes avec R. je ne sais pas comment proc?der .. en vour remerciant par avance Faouzi

...raphical output as a image and reinserting the stored image of plots through multiple ##code chunks or a code chunk executing image insert in loops.. a bit tedious i suppose!). ## Decluttering overlapping labels produced by plot.MCA and plot.MFA function in SensoMineR (Refer the functions plot.MCA2 and plot.MFA2 for this feature) ##The fastmod function includes a call to plot.MCA2 and plot.MFA2 as well so the final output is also decluttered of overlapping labels, however before calling the fastmod function a source or call to ##plot.MFA2 and plot.MCA2 is required. ## library(maptools)...