similar to: Multiple comparison test about whole population, not about mean

Hello, I am really new to R and it's still a challenge to me. Currently I'm working on my Master's Thesis. My supervisor works with SAS and is not familiar with R at all. I want to run an Anova, a tukey-test and as a result I want to have the tukey-grouping ( something like A - AB - B) I came across the HSD.test in the agricolae-package, but... unfortunately I do not get an output

Hi, I need to determinate HSD value from a matrix like that Thesis Days A1 Cx 0 66.07 Cx 0 60.24 Cx 0 42.86 Tw 0 66.07 Tw 0 60.24 Tw 0 42.86 Aa 0 66.07 Aa 0 60.24 Aa 0 42.86 Qe 0 66.07 Qe 0 60.24 Qe 0 42.86 Cx 56 310.86 Cx 56 223.17 Cx 56 186.77 Tw 56 149.42 Tw 56 127.75 Tw 56 138.59 Aa 56 130.24 Aa 56 214.83 Aa 56 137.95 Qe 56 186.64 Qe 56 189.09 Qe 56 187.87 this is my script

Hi, I did the analysis of variance of a split-plot and the effect of 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)

I am a new R user but a long time SAS user. I searched for a response to this question but no luck, so forgive me if this topic has been covered before. I am running a TukeyHSD post hoc test after running an ANOVA. I get the results of all pairwise comparisons, no problem. However, the output table is a little "busy", and I'd like to make the output easier to read. Specifically, I

Hi, I'm designing a experiment in order to compare the growing of several clones of a tree specie. It will be a complete randomized block design. How can I decide what model of mean comparision to choose? LSD, HSD,TukeyHSD, Duncan,...? Thanks in advance

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi. I have been using SAS for some time, and now I have discovered R. I am very happy with it, but I have not found out how to perform some of the multiple comparisons I was used to do in SAS. With the SAS/STAT, I generally used the MEANS (for comparison of arithmetic means) and the LSMEANS (for adjusted means) statements of the GLM procedure (I

Hi, A client has a consumption measure on each of four products. The sample size is 75. The consumption distributions are highly skewed for each product. He would like a pairwise comparison test of the products, much like Tukey's HSD but using medians rather than means. Is there such a median comparison test in R? Thanks, Walt ________________________ Walter R. Paczkowski, Ph.D.

There was a thread a little earlier in the year about maintaining the official Rails plugins. It would seem that rails_upgrade has been left by the wayside, with pull requests dating back as early as September last year. It''s mentioned in the 3.0 release notes as a way of checking your application for changes between 2.3 and 3.0, but what''s the point if the official version of it

Hi, I tried on this, but couldn't figure it out: Suppose I have a dataframe as follows: dat <- data.frame(Day=rep(rep(c(1,2), each=4),2), Animal = rep(c(1,2), each=8), Count=c(rnorm(8, 100), rnorm(8,90))) 2 animals are being examined on 2 different days. Count is the result. Now I need to point out whether or not there is a difference between the days. I did this by an ANOVA test, while

I have a model that looks like this (with various other methods) class HsdPair attr_accessor :hsd def initialize(hsd) @hsd = hsd @current_display = 0 @has_changed_flag = false end end After initializing this object in the controller @hsd_pairs = HsdPair.new(@job.hsd_pairs) using it in the view various times and in various ways, when I try to pass this object back to the

Cada vez que intento cargar el paquete "agricolae" me da el siguiente mensaje: Error: package or namespace load failed for 'agricolae' in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]): there is no package called 'spData' He intentado todo actualizar los paquetes, volverlos a instalar pero no hay forma. Si sabeis la solución ?? Un saludo. Juan

I have used the correlation analysis (pearson) in the agricolae package to analyse my data and got unexpectedly low p-values (therefore making many more highly significant correlations in my data than I had expected). I am wondering if the p-values given should be subtracted from 1 to give the real p-value, because for each variable compared against itself has a p-value of 1 and I thought it

Does anyone have a program for comparing interaction means (similar to HSD.test of agricolae) for a split or strip plot design? For those who are familiar with SAS I am looking for something similar to the DIFF option of the LSMEANS statement of PROC MIXED and the PDMIX800 macro. The diff option performs multiple mean comparison from single or factorial experiments then the macro translates the

Dear list members, I'm running some tests looking at differences between means for various levels of a factor, using Tukey's HSD method. I would like to plot the data as boxplots or dotplots, with horizontal significance lines indicating which groups are statistically significantly different, according to Tukey HSD. Here's a nice image showing an example of such a graphical

Dear all, I would be glad if someone could tell me if Tukey HSD (function of stats library) accept the NA values and could correct the unbalanced design (different number of sample in each group) Thanks for help Alice Le Bars

Dear all, W2k, R 2.5.1 I am trying out the AMMI function in the agricolae package, to analyse the dependence of environment for a certain cultivar. The function responds to four basic variables: ENV Environment GEN Genotype REP Replication Y Response My question concerns the 'REP' term. When I normally do an analysis of variance, the replication would refer to repeated observations

Hi there, I am doing multiple comparisons for data that is not normally distributed. For this purpose I tried both functions kruskal{agricolae} and kruskalmc{pgirmess}. It confuses me that these functions do not yield the same results although they are doing the same thing, don't they? Can anyone tell my why this happens and which function I can trust? kruskalmc() tells me that there are no

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

Hello everybody, I use the sweetpotato database included in R package: data(sweetpotato) This dataset contains two variables: yield(continous variable) and virus(factor variable). Due to Levene test is significant I cannot assume homogeneity of variances and I apply Welch test in R instead of one-way ANOVA followed by Tukey posthoc. Nevertheless, the problems come from when I apply posthoc

Dear list, I'd like to use path.analysis in the package agricolae in batch format on many files, retrieving the path coefficients for each run and appending them to a table. I don't see any posts in the help files about this package or the path.analysis package. I've tried creating an object out of the call to path.analysis, but no matter what I try, the function automatically prints