similar to: Proposed (minor) change to plot.TukeyHSD

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

Hello all, I would like to relate this behaviour of: plot.table & plot.TukeyHSD. They don't work with some graphical parameters. Thanks for your attetion. Cleber > ### example: > plot( table(1:10), cex.axis=0.6) > plot( table(1:10), las=2) > > tukaov <- TukeyHSD( aov(breaks ~ wool + tension, data = warpbreaks) ) > > plot( tukaov, main='xxx' ) Error

I have a question about TukeyHSD and the glht function because I'm getting different answers when a covariate is included in model for ANCOVA.? I'm using the cabbages dataset in the 'MASS' package for repeatability.? If I include HeadWt as a covariate, then I get different answers when performing multiple comparisons using TukeyHSD and the glht function. The difference appears

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

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-devel & Translation Teams, In order to monitor the progress of the translation for the pt_BR team I wrote a script to summarize the status of the translations. It wasn't difficult to extend it to the other languages so I decided to set up a page with the summaries of the translation for all languages for which currently exist a translation.

Hey, I have this TukeyHSD output from which I would like to extract only the P-values (p adj, last number). The problem is that the test output is a character list. How can I "break" this sentence to separate the Pv? Tukey multiple comparisons of means 95% family-wise confidence level Fit: aov(formula = Fe1$Fe ~ Fe1$genotype) $`Fe1$genotype` diff lwr upr

Hi, I am running a ANOVA on a factorial design, and using TukeyHSD for post hoc comparisons. I have 2 factors with three levels each: Factor B Factor A 1 2 3 1 2 3 When I look at the Tukey output (on the interaction of the factors) the comparisons come out numbered 1-36. e.g. $"A:B" diff lwr upr [1,] 49.1666667 -160.041022 258.3744 [2,]

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 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

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 list, Sorry for posting a borderline statistical question on the list, but hte SPSS people around me just stares at me blankly when refering to tests with any term other than ANOVA and post-hoc. I would appreciate any insight on how this all is possible: I have a model fitted by aov() stored in "ppdur", which gives this result when using ANOVA: > anova(ppdur) Analysis of

Dear r-useRs, After a couple of years in a 'R exile' of sorts, I've recently changed jobs and my current employer (an American multinational in the food manufacturing industry) is much more open than my past employer (which wouldn't even want to hear about anything that didn't begin with SAS...). So, after my insistence corporate IT is now considering adopting R as part of our

Dear r-useRs, After a couple of years in a 'R exile' of sorts, I've recently changed jobs and my current employer (an American multinational in the food manufacturing industry) is much more open than my past employer (which wouldn't even want to hear about anything that didn't begin with SAS...). So, after my insistence corporate IT is now considering adopting R as part of our

Dear all, I have a quite basic questions about anova analysis in R, sorry for this, but I have no clue how to explain this result. I have two datasets which are named: nmda123, nmda456. Each dataset has three samples which were measured three times. And I would like to compare means of them with Posthoc test using R, following please see the output: (CREB, mCREB and No virus are the name of

I am having what I think is a strange problem with applying TukeyHSD to an aov fit with error strata. TukeyHSD is supposed to take "A fitted model object, usually an 'aov' fit." aov (with error strata) is supposed to generate an object of type aovlist, which is a list of objects of type aov. But I can't seem to feed components of my aovlist to TukeyHSD. I guess I

I'm interested in restricting the pairwise comparisons of interaction effects in a multi-way factorial ANOVA, because I find comparisons of interactions between all different variables different to interpret. For example (supposing a p<0.10 cutoff just to be able to use this example): > summary(fm1 <- aov(breaks ~ wool*tension, data = warpbreaks)) Df Sum Sq Mean Sq F

Frank uses the term "hierarchical keyword organization" which I agree is a good way to organize a system designed to help users. In fact, this is one reason why I like the R graphics gallery which allows one to quickly find a particular type of plot based on keyword, examine the plot to see if it's close to what's desired, and then get the detailed code to examine or modify for

Hi, I'd like to know if it's possible to specify different contrast matrices in lm() for a factor that is nested within another one. This is useful when we have a model where the nested factor has a different number of levels, depending on the main factor. Let me illustrate with an example to make it clearer. Consider the following data set: set.seed(1) y <-

I have just finished translating R.pot to pt_BR and now I'll start the process of revision and will merge it with the latest SVN version (33261), as I started the translation on 02/06 (SVN 33048). There are some observations I'd like to make regarding the translation process: 1) Sometimes it is not clear in the message whether a given term is referring to an actual