similar to: Post hoc test for lm() or glm() ?

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

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:

Hi, I was trying to figure out how to do post-hoc tests for Two Way ANOVAs and found the following 2 approaches: a. Do pairwise t-tests (bonferroni corrected) if one finds significance with the ANOVA. Link- http://rtutorialseries.blogspot.com/2011/01/r-tutorial-series-two-way-anova-with.html b. Do TukeyHSD on an aov model Link-

Hallo, zur Analyse von Daten zum Artenreichtum von Pflanzen, habe ich ein Glm (glm) und anschlie?end eine Anova (anova) durchgef??hrt. Nun m??chte ich f??r die signifikanten Einflussfaktoren einen Post Hoc Tukey Test durchf??hren, um zu ermitteln in wie weit die einzelnen Faktorstufen sich signifikant voneinander unterscheiden. Mit dem Befehl (TukeyHSD) komme ich nicht

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

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

Hello, Despite my search, I didn't find a post-hoc test for an ANCOVA. I used the functions aov() and lm() to run the ANCOVA then I tried TukeyHSD() but it didn't work (because of the covariable is a continuous variable?). Furthermore, I would like to plot the adjusted values (i.e. the values of the tested variable taking into account the covariable). Thanks for your help! N. Poulet

Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

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

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.

Is there a standardized way in R to perform post-hoc comparisons for main adn interaction effects of between- and within-subject factors? For instance, I have a data set of performance of adults of different age groups (20-30, 60-70,70-80) performing a WM task (n-back, with n=1,2,3,4) in two different conditions (while sitting or walking). The corresponding ANOVA produces the following output

Hi, I have a fairly simple repeated measures-type data set I've been attempting to analyze using the lme function in the nlme package. Repeated searches here and other places lead me to believe I have specified my model correctly. However, I am having trouble with post-hoc tests. From what I gather, other people are successfully using the glht function from the multcomp package to

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 * 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

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! 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

Hi R users, I google the website and I found that there are three ways to perform repeated measure ANOVA: aov, lme and lmer. http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg58502.html But the questions are which one is good to use and how to do post-hoc test? I use the example that is provided in the above link and I try > tt<-aov(p.pa~group*time+Error(subject/time),data=P.PA)

Does anyone know of some methods already programmed up ( ie freeware : ) ) in R for the post hoc methods in anova. Particularly Scheffe's method or Tukey's? Anna