similar to: summary.lm as a post-hoc test?

Let's say I've run Anova(lm(y~a*b)) and found the a:b interaction to be significant. Now I'm interested in which specific level combinations of a and b significantly differ from the control group. Can I use the t-tests from summary(lm(y~a*b)) to answer that question? I saw no mention of multiple comparison in the documentation for summary.lm, so am I right in assuming I need to

Hi R-helpers, TukeyHSD() works for models fitted with aov(), but could anyone point me to a function that performs a similar post hoc test for models fitted with lm() or glm()? Thanks in advance, Mark

Dear Alex, I have read your question about post-hoc test: "Let's assume that according to Anova(lm(y~a*b, data=d)) the a:b interaction is significant, and I would like to know if there are specific combinations of a and b levels that differ from the control group. Are there any caveats against simply looking at the p-values in the output generated by summary(lm(y~a*b,data=d))? The

Hi! I am quiet new with R and I have some problems to perform a posthoc test with an lme model. My model is the following: >lme1<-lme(eexp~meal+time, random=~1|id,na.action=na.omit) and then i try to get a post hoc test: >summary(glht(lme1,linfct=mcp(meal="Tukey))) but I get a warning message: Erreur dans as.vector(x, mode) : argument 'mode' incorrect Thank you for your

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

Hi Suppose I have a matrix (cohort are rows and years are columns) [2000] [2001] [2002] [2003] [C1] 0.01 0.03 0.02 0.09 [C2] 0.06 0.05 0.07 0.11 [C3] 0.1 0.5 0.4 0.98 [C4] 0.7 0.6 0.2 0.77 I want to extracts the diagonals to get a matrix which looks like this (C1 becomes C2 in 2002, C2 becomes C3 in 2003

I have R version 2.11.1 I am able to run a Friedman.test, but cant do further post.hoc test. Tried running "friedman.test.with.post.hoc"etc It comes with "Error: object 'friedman.test.with.post.hoc' not found" This is after loading the packages "coin" and "multcomp" Could anyone please send in any suggestions how to ratify? -- View this message

Hi * i've done my anova anlysis but now i need post-hoc test, are these included in R ? I've a Big problem, working with people that don't like to use command-line software (but prefer something like openoffice) does someone is trying to do a usable GUI for R ? i'm reading something on R commander SciView and others but all seem to be beta. I'd like to make possible to make

I'm using lm to run an ANOVA, and would like to use Ryan's Q as my post-hoc (as recommended by Day and Quinn, 1989, Ecological Monographs). I can't seem to find any methods in the base stats package that implement this post-hoc. Is there a good package of post-hoc methods out there, or has someone written a method for Ryan's Q previously? Thanks! -Jarrett

Hi there, I've got a small question : is there any post-hoc test for Kruskal rank sum test integrated in R ? I know that the Nemenyi test is one of the post-hoc that can be used, but there's no (to by knowledge) R function for it. What should I do ? Thanks, Etienne

Hi Folks, I have been using the TukeyHSD to conduct post hoc comparisons. The challenge is I have two interacting factors, one of which has 6 levels (cover types), and the other 2 (study areas). As a result interpreting the post hoc comparisons is difficult when you get a list of every possible combination (66 of them). In grad school I was using SAS and I recall most of the post hoc tests

Is there code in R to automatically assign letters to different groups that are found to be statistically significant using a post-hoc test following an ANOVA? For example, let's say I found that relative rates of tree growth were statistically significant between tree species using an ANOVA and then I ran a TukeyHSD post-hoc test to determine which species were statistically

Post-hoc test for a zero inflated continuous data set with a tweedie distribution? I have a zero inflated continuous data set of aphid feeding duration on 10+ species of plant. I have fitted a glm model with a tweedie distribution and used anova() function to show that there is significance between the plant species. However, I would now like to perform of post-hoc test, ideally a Tukey-Kramer

Hi, is there a specific/appropriate function/package to perform post hoc tests when running a two way repeated measures anova? I'm looking for something that will be equivalent to the 'TukeyHSD()' for between subjects anova (with 'aov()'). For one way repeated measures anova, the 'pairwise.t.test()' function seems to work correctly but the results are questionable for

Hello everyone, Like a lot of people, I have been looking for functions in R doing ANOVA (ok) and performing multicomparisons (like Student-Newman-Keuls, etc.). As I have been a little bit disappointed, I have bee looking through the net for such "open source" softwares. I found one in: http://www.statpages.org/miller/openstat/OS4.html I have begun to use it, and it seems good and

Hi everybody does anyone know how I can run ANOVA post-hoc tests using R commander or R in general? Thank you Dr. Iasonas Lamprianou

Hi, I have searched and found a response to a question similar to mine but when I tried the code, R says it's not an actual function so I thought I'd ask here. http://r.789695.n4.nabble.com/file/n4633035/Cookies.csv Cookies.csv I have attached the data I am using. I am trying to look at two things: how moisture content changes over time, and how it changes along the length of a log

Hi R helpers! I have used a glht as a post-hoc test on an lmer with: -2 treatments (A & B) -1 categorical explanatory variable (song type) -1 response variable (latency to respond) I wanted to make comparisons between the categorical variables depending on treatment. At the moment the glht simply returns comparisons of each of the (3) categorical explanatory variables with each other

Hi list, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance (kruskal.test() function object). I was looking for something like the Dunn Test. I’ve searched the internet but nothing seemed to define a way to it. Do You have any suggestion? Other equivalent test maybe! Thanks in

Hi everyone, I woudl like to apply a Tukey post hoc after a repeated measure ANOVA. I followed the suggestions that I found in this help -list especially this one: /[R] Tukey HSD (or other post hoc tests) following repeated measures ANOVA You want to use lme() in package nlme, then glht() in the multcomp package. This will give you multiplicity adjusted p-values and confidence intervals.