search for: tukey

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the...

...h the patch I mailed earlier today, I found out a few adjustments could be made to the compression level settings.This retuning speeds up the encoding and improves compression, while not changing anything decoding-wise. Currently, compression settings are as follows -5, -l 8 -b 4096 -m -r 5 -A tukey(0.5) -6, -l 8 -b 4096 -m -r 6-A tukey(0.5) -7, -l 8 -b 4096 -m -e -r 6-A tukey(0.5) -8, -l 12 -b 4096 -m -e -r 6-A tukey(0.5) I suggest the following, in case my previous patch is accepted -5, -l 8 -b 4096 -m -r 5 -A tukey(0.5) -6, -l 8 -b 4096 -m -r 6-A tukey(0.5);partial_tukey(2) -7, -l 8 -b 40...

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-analys...

...rnorm(48)) require(multcomp) require(lme4) fit1<-lmer(response~treat1*treat2+(1|id),data=d.fr) temp<-expand.grid(treat1=unique(d.fr$treat1),treat2=unique(d.fr$treat2)) X<-model.matrix(~treat1*treat2,data=temp) # X gives me a matrix with the dimensions 12 by 12. glht(fit1, linfct = X) Tukey<-contrMat(table(d.fr$treat1),'Tukey') K1<-cbind(Tukey,matrix(0,nrow=nrow(Tukey),ncol=ncol(Tukey))) rownames(K1) <- paste(levels(d.fr$treat2)[1],rownames(K1), sep = ":") K2 <- cbind(matrix(0, nrow = nrow(Tukey), ncol = ncol(Tukey)), Tukey) rownames(K2) <- paste(lev...

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 (like here in the answer http://stats.stackexchange.com/questions/31547/how-to-obtain-the-results-of-a-tukey-hsd-post...

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 Tukey-correctio...

Tukey divides the points into three groups, not the x and y values separately. I'll try to get hold of the book for a direct quote, might take a couple of days. On Mon, May 29, 2017 at 8:40 AM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 27/05/2017 9:28 PM, GlenB wrote: &gt...

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 display: http://www.biomedcen...

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: summary(glht(model, linfct=mcp(Treatment=&q...

I have been trying to do tukey's test to no avail. This is what I have and the error produced: pen.df = data.frame(blend, treatment, y) source("tukey.1.r") tukey.1(aov.pen, pen.df) Error in tukey.1(aov.pen, pen.df) : the model must be two-way This is a two-way design. Therefore I am confused. Can anyone help? R...

A usually trustworthy R correspondent posted a pure R implementation on SO at some point in his lost youth: https://stackoverflow.com/questions/3224731/john-tukey-median-median-or-resistant-line-statistical-test-for-r-and-line This one does indeed generate the line of identity for the (1:9, 1:9) case, so I do suspect that we have a genuine scr*wup in line(). Notice, incidentally, that > line(1:9+rnorm(9,,1e-1),1:9+rnorm(9,,1e-1)) Call: line(1:9 + rnor...

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)...

...;A1.txt" data_table <- read.table(file, header=T, row.names=NULL) attach(data_table) anova <- aov(A1 ~ factor(Thesis)*factor(Days)) detach(data_table) first of all, I need to know if my script has conceptual errors secondly, I need to calculate HSD between Thesis:Days means I try with Tukey.test command from agricolae package, but it do not work I can use only these commands Tukey.test(anova, "Thesis") Tukey.test(anova, "Days") but not Tukey.test(anova, "Thesis*Days") how can I do? my apologies for the banal questions, but I'm taking the first st...

...ion functions that I developed. From my own test results (on quite a diverse dataset) they outperform the current best apodizations by 0.05% - 0.1% (depending on the specifics) on compression. Here's a selection of the test results *Apodization functions* ,Compres, Speed partial_tukey(2) tukey(0.5) , 56.50 , 37.2x partial_tukey(3) , 56.51 , 37.0x tukey(0.75) gauss(0.2) tukey(0.25), 56.54 , 35.8x partial_tukey(2) , 56.55 , 50.5x tukey(0.25) gauss(0.2) , 56.57 , 49.6x tukey(0.5) , 56.69 , 79.3x Speed is in...

I would like to write a function that computes Tukey's 1 df for nonadditivity. Here is a simplified version of the function I'd like to write: (m is an object created by lm): tukey.test <- function(m) { m1 <- update(m, ~.+I(predict(m)^2)) summary(m1)$coef } The t-test for the added variable is Tukey's test. This won'...

...ndividuals are treated with treatments A, B, C and D in four different occasions. Once I get a significant ANOVA, I first run a paired samples t-test using the code: t.test(X1,X2,paired=TRUE) #being x1 the punctuation after treatment 1 and x2 the punctuation after treatment 2. After this, I run a Tukey posthoc test for repeated measures as stated in gribblelab: require(nlme) a1<-lme(x~factortmnt,random=~1|factorid/factortmnt,data=mydata) print(anova(a1)) require(multcomp) summary(glht(a1,linfct=mcp(factortmnt="Tukey"))) The fact is that once I get both results, there are some occa...

...vorite email program and send it to # # r-bugs at r-project.org # ###################################################### This report is joint from Richard Heiberger <rmh at temple.edu> and Burt Holland <bholland at temple.edu>. Burt Holland is the coauthor of the paper that the ?ptukey documentation references. R was used to run an example in our elementary Stat course. It was a one-way ANOVA, the factor `strategy' having 3 levels Price, Quality and Convenience. We issued the command summary(simint(sales ~ strategy, type="Tukey", data=Xm15.01s)) and receiv...

...omaL") tapply(data$value, list(Product=data$Product), mean, na.rm=TRUE) model <- lme(value ~ Product+Time+Arm+Product*Arm+Product*Time+Product*Arm*Time, random = ~1 | Subj,data =data) summary(model) x<-anova(model) x library(multcomp) su<-summary(glht(model,linfct=mcp(Product="Tukey"))) ##length(su) ##su[1:(length(su)-4)] x11() plot(summary(glht(model,linfct=mcp(Product="Tukey"))),cex.axis=0.6) ##For Each Product Comparison across All Time Points. data<-MyData data<-subset(data,Product=="a") tapply(data$value, list(Time=data$Time), mean, na.r...

> Tukey divides the points into three groups, not the x and y values separately. > I'll try to get hold of the book for a direct quote, might take a couple of days. Ah well, I can't get it for a week. But the fact that it's often called Tukey's three group line (try a search on *tukey...

...t;/span>, <span class="argument">--compression-level-6</span> </td> <td> - Synonymous with <span class="argument">-l 8 -b 4096 -m -r 6</span> + Synonymous with <span class="argument">-l 8 -b 4096 -m -r 6 -A tukey(0.5);partial_tukey(2)</span> </td> </tr> <tr> @@ -807,7 +807,7 @@ <span class="argument">-7</span>, <span class="argument">--compression-level-7</span> </td> <td> - Synonymous with <s...