similar to: Which function to use for multiple comparison?

I have insect data from twelve sites and like most environmental data it is non-normal mostly. I would like to preform an anova and a means seperation like tukey's HSD in a nonparametric sense (on some sort of central tendency measure - median?). I am searching around at this time on the internet. Any suggestions, books, etc. would be greatly appreciated. -- Stephen Sefick Research

Is there a fonction for multiple comparison tests (similar to "multicomp" in Splus) in a package of R? Thanks in advance for any hint... Cheers, Patrick Giraudoux University of Franche-Comté Department of Environmental Biology EA3184 af. INRA F-25030 Besançon Cedex tel.: +33 381 665 745 fax.: +33 381 665 797 http://lbe.univ-fcomte.fr [[alternative HTML version deleted]]

So I've come across a few cases where complex outputs from functions will not write to tables. The most recent case involves the TukeyHSD function in the stats package. If I save the TukeyHSD call and print it, that obviously goes fine, but when I try writing to a table, I get an error message that says "cannot coerce class \multicomp\" into dataframe. What does this mean, and

Hello, Is there an option I can easily set to put labels next to the points in a simple plot? The closest I got to it was to use the option pch, but this replaces the point symbol with the character specified, and it is not what I want. Thanks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear all, I am trying to use the rstable(n, alpha, beta, gamma = 1, delta = 0, pm = c(0, 1, 2))) function to generate positive stable random numbers. For positive stable distribution, beta==1 and alpha is in (0,1), which defines random variables with support (0, infinity). So, I used rstable(100, 0.5, 1) for an example. I found that this gives me some negative numbers. For example, >

Dear R-listers, I am trying to compute simultaneous confidence intervals with simint from the package multcomp. 230 measures (abundance) have been taken in 23 sites (factor) of a data.frame (donnees: a file can be sent on request, saved with save(donnees,file="donnees")). I would like to get all pairwise comparisons with : mc<- simint(ren~ID,type="Tukey",data=donnees) I

Hi folks, sorry if this has been answered before, I searched long and hard before deciding to make a thread. I'm trying to include multiple variables in a non-parametric analysis (hah!). So far what I've managed to figure out is that the NPMC package from CRAN MIGHT be able to do what I need, but I can't get it to. First I created a dataset as NPMC calls for. > Ind=Individual

Hello, Despite my search, I didn't find a post-hoc test for an ANCOVA. I used the functions aov() and lm() to run the ANCOVA then I tried TukeyHSD() but it didn't work (because of the covariable is a continuous variable?). Furthermore, I would like to plot the adjusted values (i.e. the values of the tested variable taking into account the covariable). Thanks for your help! N. Poulet

Hello, (maybe a quite basic statistical question, but I'm just struggling with it) I'm doing an anova: > Res1<-aov(H2O~location+topo+horizon+pF+Error(location:topo:horizon)) (water retention of soils) which gives a significant difference at factor "location". Which function should I use to now which locations (there are 3: A, B and C) differ significantly and which do

Hello everyone, So I ran an anova with aov and then I want to run post-hoc comparisons but keep receiving this message : > no applicable method for "TukeyHSD" Here is my code: > d<-read.table("d.txt") > d > Obs subj Hand Gaze RT > 1 1 s1 1 1 401.4 > 2 2 s2 1 1 363.3...... > summary(ano <-

I'm trying to do an ANCOVA with two factors (clipping treatment with two levels, and plot with 4 levels) and a covariate (stem diameter). The response variable is fruit number. The minimal adequate model looks like this: model3<-lm(fruit~clip + plot + st.dia + clip:plot) I'd like to get some multiple comparisons like the ones from TukeyHSD, but TukeyHSD doesn't work with the

Hi, I sent an earlier message concerning this, but perhaps I wasn't clear enough. Up until about a month ago, I downloaded packages by clicking on the filename of the package. Now this action leads me to a directory listing, e.g.: drwxr-xr-x hornik/users 0 2002-03-20 18:00:54 npmc/ -rw-r--r-- hornik/users 314 2002-03-20 11:33:42 npmc/DESCRIPTION -rw-r--r-- hornik/users 202

Dear R-developeRs, Attached follows a patch against svn 34959 that adds the printing of p-values to the TukeyHSD.aov function in stats package. I also updated the corresponding documentation file and added a 'see also' reference to the simint function of the multcomp package. As it was already brought up in a previous thread [1] in R-help, one can obtain the adjusted

HI, I am a new user of R and want to analyse some data using npmc. My data have several levels of factor (Site, Year and Season) and several variable (Percentages). I have tried to use npmc but I always get an error message. My data are in a table following this example: Site YEar Season Var1 Var2 .... A 2009 Dry 10 56 B ........ here is the error

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

Quisiera agrandar el eje de ordenadas en un diagrama de lineas.. para que haya más espacio entre punto y punto y "se noten mejor las diferencias"... ¿alguna sugerencia? -- Antonio Maurandi

Dear useRs, I'm working on multiple comparison design on two factor (2 3 levels) ANOVA. Each of the tests I have tried (Tukey, multcomp package) seem to do only with one factor at a time. fm1 <- aov(breaks ~ wool * tension, data = warpbreaks) tHSD <- TukeyHSD(fm1, "tension", ordered = FALSE) $tension diff lwr upr p adj M-L -10.000000 -19.35342

Hi there, I am having a problem with package npmc. If I use the included datasets (brain, kronen) everything is fine, but if I try and use my dataset I receive an error message: Error in probval.GenzBretz(algorithm, n, df, lower, upper, infin, corr, : NAs in foreign function call (arg 2) In addition: Warning message: In probval.GenzBretz(algorithm, n, df, lower, upper, infin, corr, : NAs

Hi, I'm having trouble getting the function `npmc' working. I have a 2 column 30 row table called `mydata': > npmc(mydata, df=2, alpha=0.05) Error in sort(unique.default(x), na.last = TRUE) : `x' must be atomic > is.atomic(mydata) [1] TRUE Is there anything I have overlooked? Am I invoking the function correctly? I wasn't able to find any hints in the archives

Hi Does anyone know where is the package: npmc (Nonparametric Multiple Comparisons). I found the reference on R Site Search, but not the package itself on CRAN as suggested. Thanks Mauricio