similar to: anova and tukeyHSD

Hello R People: Here's the Saturday night goofy question. I would like to see the code for TukeyHSD function and I tried the following: > getAnywhere("TukeyHSD") A single object matching ?TukeyHSD? was found It was found in the following places package:stats namespace:stats with value function (x, which, ordered = FALSE, conf.level = 0.95, ...)

I can prove I've done this before, but I recently installed Rexcel (and it was easiest to reinstall R and some other bits to make it work) and now its no longer working. Before I would do an ANOVA and a tukey post-hoc like this: >data1.aov=aov(result~factor1*factor2, data=data1) then... >TukeyHSD(summary(data1.aov)) and it would give me a nice tukey table of all the pairwise

Dear R-Helpers, I was calling the TukeyHSD function and not getting confidence intervals or p-values. It turns out this was caused by missing data and the fact that I had previously turned on R Commander (Rcmdr). John Fox knew that Rcmdr sets na.action to na.exclude, which causes the problem. If you have this problem, you can either exit Rcmdr before calling TukeyHSD or you can set na.action to

Hello, When plotting the results of a TukeyHSD multiple comparisons procedure with an ANOVA (lm) object, an extra line appears in the confidence intervals that contain 0. For example (this is straight from the TukeyHSD helpfile): > summary(fm1 <- aov(breaks ~ wool + tension, data = warpbreaks)) > TukeyHSD(fm1, "tension", ordered = TRUE) > plot(TukeyHSD(fm1,

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:

pairwise.t.test is returning NAs when one of the samples only has one entry, while TukeyHSD returns results (maybe not trustworthy or believable, but results). I stumbled on this because I did not realize one of my samples only had one entry while most of the others had several hundred, so I realize this is not a desirable situation. I'm really just curious about the difference between how

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 <-

Why do I see this error? > library(stats) > require(stats) [1] TRUE > > tHSD <- TukeyHSD(aov) Error in TukeyHSD(aov) : no applicable method for "TukeyHSD" In case it helps: > aov Call: aov(formula = roi ~ (Cue * Hemisphere) + Error(Subject/(Cue * Hemisphere)), data = roiDataframe) Grand Mean: 8.195069 Stratum 1: Subject Terms: Residuals Sum

Dear R people, I have a couple of questions about post-doc analyses for 2 by 2 within subjects ANOVA. I conducted a psycholinguistic study that combined a 2 by 2 design and a latin square design. Specifically, I had 32 items each of which generated 4 conditions. Participants saw each of the 32 items only once: 8 in Condition A, 8 in B, 8 in C, and 8 in D. The table below serves as an example.

Hi, I am seeking help with an error when running the example from R Documentation for TukeyHSD. The error occurs with any example I run, from any text book or website. thank you... > plot(TukeyHSD(fm1, "tension")). Error in plot(confint(as.glht(x)), ylim = c(0.5, n.contrasts + 0.5), ...) : error in evaluating the argument 'x' in selecting a method for function

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

I've tried to run a Tukey post-hoc but keep getting this weird error, whether the aov was significant or not. treat_code is a dummy variable, but that shouldn't matter. Any suggestions? Thanks Amy > summary(aov(EtoH~treat_code, mydata)) Df Sum Sq Mean Sq F value Pr(>F) treat_code 1 16.44 16.44 11.027 0.001014 ** Residuals 287 427.91 1.49 --- Signif.

Hello R Developers, Dear R-developers, I ran some standard tests with currently (today morning) compiled R release candidate in Linux R 2.12.1 RC (2010-12-13 r53843). Some of these tests used plot.TukeyHSD function. This worked OK on the screen (X11 device), but PostScript file could not be rendered. The following example had the problem with me: postscript(file="tukeyplot.ps")

Dear r-help members. I would like to compare species numbers of moths between eight different forests (each sampled for six nights). I would like to do a nested anova to compare species numbers between forests and nights. For more site specific details I wanted to do a Tukey test (TukeyHSD). Unfortunately this test is not working (message: "nicht anwendbare Methode f?r 'TukeyHSD' auf

Hi all, I search the archive for finding a simple solution for using TukeyHSD with a multistratum aov result (a repeated emasure anova). The Question have been asked but I've found no clear answer. res<-aov(y~Fa*Fb+Error(Subject/(Fa*Fb)) ) I think that the problem is that res is an aovlist object instead of the "aov" object required by TukeyHSD. Is there an easy solution to

Howdo folks, So I have my data (attached). There are two columns I'm interested in; "algname" and "dur". I'd like to know how dur changes with algname. algname is nominal and there are 7 possibilities. There are two more nominal independents, "task" and "id", so my model is: dur ~ algname+task+id From the research I've done, a TukeyHSD

Hi, the function TukeyHSD gives incorrect results for balanced incomplete block designs, as the example below shows, but I can only half fix it. There are two problems, 1. It uses model.tables to estimate treatment means, 2. It uses the wrong standard error The first problem can be fixed using dummy.coef, if the lines > TukeyHSD.aov function (x, which = seq(along = tabs), ordered = FALSE,

Dear Help List, Thanks in advance for reading...I hope my questions are not too ignorant. I have an experiment looking at evolution of wing size [centroid] in fruitflies and the effect of 6 different experimental treatments [treatment]. I have five replicate populations [replic] in each treatment and have reared the flies in two different temperatures [cond] to assay the wing size, making

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

Dear R gurus, I have the following model: appcov.aov <- aov(yield ~ prevyield + trt + block) where prevyield is a continuous numeric covariate and trt and block are factors (yes, I did factor()!) Now, when I do a TukeyHSD, my diff's are all screwed up! For instance: treatment mean for treatmen "E" is 277.25 and for treatment "O" is 279.5, so I figure the diff O-E