similar to: : Experimental Design

I am not sure if my message made it through, so here it is again! Hi Rer's, R-1.1.0 I have two questions for you: 1) I am trying to complete a multiple comparison test after completing a one-way ANOVA on some data. I think this is pretty reasonable. aov(MetricSubset ~ GeneNameFactor) works pairwise.t.test(MetricSubset,GeneNameSubset,p.adjuxt.method=bonferroni,p ool.sd=FALSE)

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-

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 have a simple dataset with repeated measures. one factor is treatment with 3 levels (treatment1, treatment2 and control), the other factor is time (15 time points). Each treatment group has 10 subjects with each followed up at each time points, the response variable is numeric, serum protein amount. So the between subject factor is treatment, and the within subject factor is time. I ran a

[Moderator: This was erronously sent to R-announce, and filtered fortunately ] Hi, This is my first time to use R. I'm wondering which function I can use to do multiple comparison. I have an lm object and want to do multiple comparison based on this object. Splus has a function multicomp() but I could not find a similar one in R. Thanks in advance. Really appreciate it. Julie

Dear all, I need to understand a thing in the beheaviour of the two functions aov and anova in the following case involving an analysis of ANOVA with repeated measures: If I use the folowing command I don´t get any problem: >aov1 = aov(response ~ stimulus*condition + Error(subject/(stimulus*condition)), >data=scrd) > summary(aov1) Instead if I try to fit the same model for the

Hello, (maybe a quite basic statistical question, but I'm just struggling with it) I'm doing an anova: > Res1<-aov(H2O~location+topo+horizon+pF+Error(location:topo:horizon)) (water retention of soils) which gives a significant difference at factor "location". Which function should I use to now which locations (there are 3: A, B and C) differ significantly and which do

Hi R-help members, I have read a lot in the Archive about the "Type I" vs "Type III" sum of square. I think I have read confusing post so I want to have a clear idea of the problem. Here is an example. I have 3 groups of subjects of unequal sample size (G1 (n=7), G2 (n=7), G3 (n=4)). for Each subject I have 4 measures corresponding to the crossing of 2 factor (A & B)

Dear all, I am studying a dataset using the aov() function. The independant variable 'cds' is a factor() with 8 levels and here is the result in studying the dependant variable 'rta' with aov() : > summary(aov(rta ~ cds)) Df Sum Sq Mean Sq F value Pr(>F) cds 7 0.34713 0.04959 2.3807 0.02777 Residuals 92 1.91635 0.02083 The dependant variable

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 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

Hello, Is there an option I can easily set to put labels next to the points in a simple plot? The closest I got to it was to use the option pch, but this replaces the point symbol with the character specified, and it is not what I want. Thanks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear R-help, I have a question about pairwise.t.test and adjustment for multiple comparisons for paired data points. I have the following data: n=c("x", "x", "x", "x", "x", "x", "x", "x", "x", "x", "y", "y", "y", "y", "y", "y",

Hi all, I'm new to R and have the following problem: I have a 2 factor design (a has 2 levels, b has 3 levels). I have an object kidney.aov which is an aov(y ~ a*b), and when I ask for model.tables(kidney.avo, se=T) I get the following message along with the table of effects: Design is unbalanced - use se.contrast() for se's but the design is NOT unbalanced... each fator level

Hello. I have come across a curious result that I cannot explain. Hopefully, someone can explain this. I am doing a 1-way ANOVA with 6 groups (example: summary(aov(y~A)) with A having 6 levels). I get an F of 0.899 with 5 and 15 df (p=0.51). I then do the same analysis but using data only corresponding to groups 5 and 6. This is, of course, equivalent to a t-test. I now get an F of 142.3

I am using R for a class which uses S. Often I can not find functions that in S but not in R, example, multicomp(). What is your advise. Thanks. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Hi there, I am trying to do multiple pairwise Wilcoxon signed rank tests in a manner similar to: a <- c(runif(1000, min=1,max=50), rnorm(1000, 50), rnorm(1000, 49.9, 0.5), rgeom(1000, 0.5)) b <- c(rep("group_a", 1000), rep("group_b", 1000), rep("group_c", 1000), rep("group_d", 1000)) pairwise.wilcox.test(a, b, alternative="two.sided",

Hi r lovers! I 'd like to apply the cor() function to a matrix which have some missing values As a matter of fact and quite logically indeed it doesn't work Is there a trick to replace the missing value by the mean of each variable or by any other relevant figures ? Or should I apply a special derivate of the cor() function, (I don't have any idea if it exists and have some trouble to

I am interested in a statistical comparison of multiple (5) time series' generated from modeling software (Hydrologic Simulation Program Fortran). The model output simulates daily bacteria concentration in a stream. The multiple time series' are a result of varying our representation of the stream within the model. Our main question is: Do the different methods used to represent a

I am analyzing some data obtained after measuring some parameters at different times in samples obtained from many subjects. The model is quite simple: aov(parameter ~ Time + Error(Subject/Time)) Now I want to make a pairwise comparison between the levels of Time. However, I have not find how to do such a thing. I cannot use TukeyHSD or pairwise.t.test, I supposse. Maybe using contrasts? Could