similar to: Tukey HSD plot with lines indicating (non-)significance

Hi everyone I'm using Tukey HSD as post-hoc test following a lme analysis. I'm measuring hemicelluloses in different species treated with three different CO2 concentrations (l=low, m=medium, h=high). The whole experiment is a split-plot design and the Tukey-function from the package multcomp is suitable for lme-analysis with random factors. The analysis works fine but I get a non

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

I am trying to do Tukey HSD comparisons on a repeated measures expt. I found the following example on r-help and quoted approvingly elsewhere. It is broken. Can anyone please tell me how to get it to work? I am using R 2.4.1. > require(MASS) ## for oats data set > require(nlme) ## for lme() > require(multcomp) ## for multiple comparison stuff > Aov.mod <- aov(Y ~ N + V +

Hello, I am trying to determine the most appropriate way to run post-hoc comparisons on my lme model. I had originally planned to use Tukey HSD method as I am interested in all possible comparisons between my treatment levels. TukeyHSD, however, does not work with lme. The only other code that I was able to find, and which also seems to be widely used, is glht specified with Tukey:

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

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 Is there any way of doing a Tukey HSD post-hoc test after a Kruskal- Wallis or Friedman rank sum test (in the ctest package)? Thanks in advance, Albertus Dr. Albertus J. Smit Department of Botany University of Cape Town Private Bag Rondebosch 7700 South Africa Tel. +27 21 689 3032

Hey Folks: New to R and learning as I go, but really, I know just enough to get myself into trouble. I've waded through everything up till now, and don't see anything in the search that is directly helpful for the POS that I've created. The GOAL: All I want in the world is a program that performs 1-way ANOVA's on every column in a data set (taking the first column as the

Dear *, I would like to obtain for each factor of my anova model the "response variable vs factor" plot with means and 95% Tukey HSD intervals. I would appreciate any information on how to do that. Cheers -------------------------------------------------------------------- Max MANFRIN Tel.: +32 (0)2 650 3168 IRIDIA - CoDE, CP 194/6

Dear all, I am doing a one way between subjects anova in an unbalanced data set. Suppose we have "a" levels of the one factor. I want to merge the not so significantly different levels into the same cluster. Can I do a Tukey Kramer HSD and then use the following algorithm: For i in 2 : "a" For j in 1 : i-1 if mean of level i is not significantly different

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'm trying to make sense of the options for multiple comparisons options in R. I've found the following options: pairwise.t.test, which provides standard t-tests, with options for choosing an appropriate correction for multiple comparisons TukeyHSD, which provides the usual Tukey test glht(package multcomp), which provides a variety of options >From the help list, it appears

Hi, I was wondering if you could help me: The following are the first few lines of my data set: subject group condition depvar s1 c ver 114.87 s1 c feet 114.87 s1 c body 114.87 s2 c ver 73.54 s2 c feet 64.32 s2 c body 61.39 s3 a ver 114.87 s3 a feet 97.21 s3 a body 103.31 etc. I entered the following ANOVA command: >dat <- read.table("mydata.txt", header=T)

dear all effect of a, b and c on d, total 48 comparisons, got one anova result in model1=aov(d~A*B*C). can we get all the result in one command? or can we interpret the whole comparisons from this result? how it work in Tukey HSD? jose ____________________________________________________________________________________ Access over 1 million songs.

Drug US1 US2 Aptecha Celebrex 235.54 269.99 121.02 Detrol LA 157.99 190.99 55.3 Flomax 166.00 190.99 93.45 Lipitor 174.99 200.99 137.7 Novaldex 108.6 129.99 22.48 Norvasc 186.66 203.99 161.93 Plavix 107.99 106.99 64.53 Prevacid 117.39 134.99 59.83 Prilosec 115.99 126.99 57.75 Zyrtec 181.1 200.99 58.79 US1=c(235.54,157.99,166,174.99,108.60,186.66,107.99,117.39,115.99,181.10)

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

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)

Dear R community, I compare mean monthly body temperature between two age classes of turtles overwintering underground. lm(body_tem ~ Month*Year*Age_Class) TukeyHSD(aov(body_tem ~ Month*Year*Age_Class, a)) The Tukey HSD as well as the planned contrasts method showed significant differences between the two age classes, but insignificant differences between the two age classes at the same

Hello, I am a little out of date and am still using S-Plus instead of R. I haven't been able to find the right place to ask this question, so I thought I would ask it here and hope that someone can help. I am unable to located the TukeyHSD() function in S-Plus. I have been able to use the GUI to run Tukey's test, but the results don't provide a p-value. Does anyone know how I can

Hi all!