similar to: What is the difference between anova {stats} and aov?

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

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 useRs, I'm working on multiple comparison design on two factor (2 3 levels) ANOVA. Each of the tests I have tried (Tukey, multcomp package) seem to do only with one factor at a time. fm1 <- aov(breaks ~ wool * tension, data = warpbreaks) tHSD <- TukeyHSD(fm1, "tension", ordered = FALSE) $tension diff lwr upr p adj M-L -10.000000 -19.35342

Hello, I have some data in a data.frame where for each of a number of subjects, I have scores for all of a number of symptoms. Subjects are subdivided in a number of groups, which have unequal sizes. I'd like to plot between-group differences in the scores on the various symptoms. Ideally, that would be in a form as would be produced by > bwplot( Score~Symptom ) but I'm not sure

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 all!

Hello, R-i-zens. I'm working on an data set with a factorial ANOVA that has a significant interaction. I'm interested in seeing whether the simple effects are different from 0, and I'm pondering how to do this. So, I have my.anova<-lm(response ~ trtA*trtB) The output for which gives me a number of coefficients and whether they are different from 0. However, I want the

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, I am performing a BACI analysis with ANOVA using the following glm: fit1<-glm(log(Cucs_m+1)~(BA*Otter)+BA+Otter+ID+Primary, data=b1) The summary(aov(fit1)) shows significance in the interaction; however, now I would like to determine what combinations of BA and Otter are significantly different (each factor has two levels). ID and PRIMARY substrates are categorical and included in

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,

Quick question, as I attempt to learn R. For post-hoc tests 1) Is there an easy function that will take, say the results of tukeyHSD and create a grouping table. e.g., if I have treatments 1, 2, and 3, with 1 and 2 being statistically the same and 3 being different from both Group Treatment A 1 A 2 B 3 2) I've been stumbling over the proper syntax for simple effects for a tukeyHSD

Hello, I would like to do a large number of e.g. 1000 paired ttest using the by-function. But instead of using only the data within the 1000 groups, R caclulates 1000 times the ttest for the full data set(The same happens with Wilcoxon test). However, the by-function works fine with the lme function. Did I just miss something or is it really not working? If not, is there any other possibility to

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

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

Dear Ashim, Try spreadLevelPlot(breaks ~ interaction(tension, wool), data=warpbreaks) . I hope this helps, John ----------------------------- John Fox, Professor Emeritus McMaster University Hamilton, Ontario, Canada Web: socialsciences.mcmaster.ca/jfox/ > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Ashim > Kapoor > Sent:

I have a specific question and a general question. Specific Question: I want to do an analysis on a data frame by 2 or more class variables (i.e., use 2 or more columns in a dataframe to do statistical classing). Coming from SAS, I'm used to being able to take a data set and have the output of the analysis in a dataset for further manipulation. I have a data set with vote totals, with one

Hi all: I have a quesion about ANOVA: Is SS(Sum of Square) of a specific factor constant with the number of factors changing? dat1 includes one factor g1,and g1's SS is called SS_g1_dat1. dat2 includes two factors g1,g2,and g1's SS is called SS_g1_dat2. My quesion is: Is SS_g1_dat1 equals to SS_g1_dat2? I have both "yes" and "no" reasons for the quesion,but

Dear All, I want a transformation which will make the spread of the response at all combinations of 2 factors the same. See for example : boxplot(breaks ~ tension * wool, warpbreaks) The closest I can do is : spreadLevelPlot(breaks ~tension , warpbreaks) spreadLevelPlot(breaks ~ wool , warpbreaks) I want to do : spreadLevelPlot(breaks ~tension * wool, warpbreaks) But I get : >

Hi all, I'm demonstrating a block entry regression using R for my regression class. For each block, I get the R**2 and the associated F. I do this with separate regressions adding the next block in and then get the results by writing separate summary() statements for each regression. Is there a more convenient way to do this and also to get the change in R**2 and associated F test for

Dear Sir, Many thanks for your reply. I have a query. I have a whole set of distributions which should be made normal / homoscedastic. Take for instance the warpbreaks data set. We have the following boxplots for the warpbreaks dataset: a. boxplot(breaks ~ wool) b. boxplot(breaks ~ tension) c. boxplot(breaks ~ interaction(wool,tension)) d. boxplot(breaks ~ wool @ each level of tension) e.