similar to: one-way ANOVA model, with one factor, an unbalanced design and unequal variances

Hello - I am fairly new to R, (i.e., ability to create functions/write programs insignificant) and was wondering if there might be a convenient way to model the following: I want to fit a gaussian glm to grouped data, while allowing for unequal variances in each of the groups. More specifically, my data set looks something like this: ---------------- data group 1 76 1 2 82 1 3

Hi all, I apologize for what might be a silly question. I am interested in doing a one way anova. This is not too hard in and of itself, either with anova, aov or oneway.test . However, I need to 1) get pvalues, 2) do a posthoc analysis with Tukey HSD, 3) and have (sometimes) an unbalanced design. I just can't seem to put all the pieces together. Any suggestions? Thanks in advance, Dan.

Well fellow R users, I throw myself on your mercy. Help me, the unworthy, satisfy my employer, the ungrateful. My feeble ramblings follow... I've searched R-Help, the R Website and done a GOOGLE without success for a one way ANOVA procedure to analyse data that are both non-normal in nature and which exhibit unequal variances and unequal sample sizes across the 4 treatment levels. My

Hello, I have some patient data for my masters thesis with three groups (n=16, 19 & 20) I have completed compiling the results of 7 tests, for which one of these tests the variances are unequal. I wish to perform an ANOVA between the three groups but for the one test with unequal variance (<0.001 by both bartlett and levene's test) I am not sure what to do. I thought i would run

Dear all, I need an help because I am really not able to find over internet a good example in R to analyze an unbalanced table with Anova with repeated measures. For unbalanced table I mean that the questions are not answered all by the same number of subjects. For a balanced case I would use the command aov1 = aov(response ~ stimulus*condition + Error(subject/(stimulus*condition)), data=scrd)

Dear friends, two years ago (as I found on the web) Paul sent the following message but I was not able to find if he got an answer. Today I have the same question and it would be great if I could find out that this test has been implemented (somehow) in R. Please do not confuse it with the Brown-Forsythe test of equality of variances. Thank you: I've been searching around for a function for

Hi I am attempting Anova analysis to compare results from four groups (Samp1-4) which are lists of intensities from the experiment. I am doing this by first creating a structured list of the data and then conducting the ANOVA (Script provided below). Im an R beginner so am not sure if I am using this correctly. Two major questions I have are: 1) Is using the code (zzz.aov <- aov(Intensity ~

Hello, I'm wondering what's the best way to analyse an unbalanced design with a low number of replicates. I'm not a statistician, and I'm looking for some direction for this problem. I've a 2 factor design: Factor batch with 3 levels, and factor dose within each batch with 5 levels. Dose level 1 in batch one is replicated 4 times, level 3 is replicated only 2 times. all

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

Dear R-list! My question is related to an Anova including within and between subject factors and unequal group sizes. Here is a minimal example of what I did: library(car) within1 <- c(1,2,3,4,5,6,4,5,3,2); within2 <- c(3,4,3,4,3,4,3,4,5,4) values <- data.frame(w1 = within1, w2 = within2) values <- as.matrix(values) between <- factor(c(rep(1,4), rep(2,6))) betweenanova <-

Hello everyone: I'm a new member of this group. I have a question about "oneway.test". When I use "anova(lm(....))" to analysis the ANOVA, I can get the information about Sum Sq and Mean Sq. (The R code and the results are as follows.)

My apologies for not including the transcript in the original message: > xx <- rep(2.10,80) > groups.balanced <- as.factor(c(rep("one",40),rep("two",40))) > groups.unbalanced <- as.factor(c(rep("one",44),rep("two",36))) > t.test(xx ~ groups.balanced) Welch Two Sample t-test data: xx by groups.balanced t = 0, df = 78, p-value = 1

Hello, For an experiment, I selected plots of land within a forest either with honeysuckle or without honeysuckle. Thus, my main factor is fixed, with 2 levels: "honeysuckle present"(n=11) and "honeysuckle absent"(n=8). Within each plot of land, I have a "trenched" subplot and an "untrenched" subplot. Within each subplot of every plot, I measured soil

I found this paper on ANOVA on unequal error variance. Has this be incorporated to any R package? Is there any textbook that discuss the problem of ANOVA on unequal error variance in general? http://www.jstor.org/stable/2532947?cookieSet=1

Dear R people: I wish to switch from SPSS to R, but there is one particular type of ANOVA design that cannot be done in R. Or more likely, it can be done, but it is nowhere documented. The problem is typical for psychologists: You have a repeated measures design with different groups of subjects. Now, this can be done with the aov command, but the number of subjects in both groups must be

Hi I am trying to run an ANOVA on data with unequal variance. I am new to nlme, but to my understanding I need to use the gls function. I have single response variable (distance which is continuous) and the explanatory variable is individual ID (class variable: individuals differ in the variance in their distance values hence the need to using nlme). So I would create a model

Hello all, This may be a simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas with unbalanced design in R. In my case, I have 11 vegetation transects (with 1000 10cmx10cm squares), where we estimated shrub cover. We have two different treatments: wildfire (4 transects) and prescribed burning (7 transects) and we want to

I have a three-way unbalanced ANOVA that I need to calculate (fixed effects plus interactions, no random effects). But word has it that aov() is good only for balanced designs. I have seen a number of different recommendations for working with unbalanced designs, but they seem to differ widely (car, nlme, lme4, etc.). So I would like to know what is the best or most usual way to go about working

# users would benefit from a warning about the behavior in the # groups.unbalanced case below. A propogation of difference is the variance # calculation is leading to an apparently significant difference in # means, even though the numeric values are all identical. Obviously upon # inspection the difference in means is meaningless, but users might be warned # if all of the input data is

Hello Using R 2.2.1 on a Windows machine. Has anyone programmed the Welch test for equality of variances? I tried RSiteSearch, but this gave references to t test and oneway.test, which are not quite what I need.....I need the Welch test itself, for use in a meta-analysis (to determine if variances are equal). TIA Peter Peter L. Flom, PhD Assistant Director, Statistics and Data Analysis