similar to: Gaussian glm for grouped data with unequal variances

Hi, i'm looking for an R function to fit a one-way ANOVA with one factor containing 10 levels. The factor levels have different numbers of observations (varying between 20 to 40). For most of the dependent variables i'm testing there are unequal variances among the factor levels. I see the function oneway.test: oneway.test(variable ~ factor, data=dataset) which by default does not

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 R-help, I am trying to set up linear mixed effects models in R using the (recommended) nlme package (R version 2.3.1 on a Linux platform). When trying to reproduce an example from Jose Pinheiro & Douglas Bates (2000, p 210) I get the following error message (code to produce message pasted as well): library("nlme") data("Orthodont") vf1Ident <- varIdent(

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

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

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 ~

Dear R-help: Does anyone know of a package in R that will do Welch's modified F-test for heterogeneous error variances? Are there other statistical techniques available in R that test the equality of means when homoscedastisity is violated? 't.test' does this in the pairwise sense when var.equal = TRUE. With best wishes and kind regards I am Sincerely, Corey A. Moffet Support

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.)

Dear Douglas and R-help, Does lme assume normal distribution AND equal variance among groups like anova() does? If it does, is there any method like unequal variance T-test (Welch T) in lme when each group has unequal variance in my data? Thanks, Shirley

Hi all, I have probably a basic question, but I can't seem to find the answer in the literature or in the R-archives. I would like to do a robust ANCOVA (using either rlm or lmRob of the MASS and robust packages) - my response variable deviates slightly from normal and I have some "outliers". The data consist of 2 factor variables and 3-5 covariates (fdepending on the model).

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 all, right now i am simply comparing means. obviously this can be done by the simple t.test respectively the welch test, if var.equal is set to FALSE. just like this t.test( Y ~ group) t.test( Y ~ group, var.equal = FALSE) now that i need to compare weighted means i am using the lm function as an adjusted t-test: like lmtest <- ( Y ~ group ) anova(lmtest)

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

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

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

>From basic statistics principle,we know,given several i.i.d Gaussian RVs with zero or nonzero mean,the sum of square of them is a central or noncentral Chi-distributed RV.However if these Gaussian RVs have different variances,what does the sum of square of them obey? Thanks in advance.

This is a relatively recent article that is somewhat accessible. Jensen, D. R., and Solomon, Herbert (1994), "Approximations to joint distributions of definite quadratic forms", Journal of the American Statistical Association, 89 , 480-486 It has references to previous work. I also have an old paper that is so old I can't tell what journal it came out of:( Grad, Arthur and Solomon,

Hi, I am encountering a difficulty I don't understand. Be patient, I'm very new to analysis of variance. If I load this data: example12_7=read.table("http://msemac.redwoods.edu/~darnold/math15/data/chapter12/example12_7.dat",header=TRUE) The run the oneway.test: oneway.test(time~drug,data=example12_7,var.equal=TRUE) I get these results: data: time and drug F = 4.1881, num

Hello everybody, I use the sweetpotato database included in R package: data(sweetpotato) This dataset contains two variables: yield(continous variable) and virus(factor variable). Due to Levene test is significant I cannot assume homogeneity of variances and I apply Welch test in R instead of one-way ANOVA followed by Tukey posthoc. Nevertheless, the problems come from when I apply posthoc

I'am trying to develop some code if R, which would correspond to what I did in SAS. The data look like: Treatment Replicate group1 GSI Control A 1 0.81301 Control B 1 1.06061 Control C 1 1.26350 Control D 1 0.93284 Low A 2 0.79359 Low B