similar to: Simple Questions

I've been searching around for a function for computing the Brown-Forsythe F* statistic which is a substitute for the normal ANOVA F statistic for when there are unequal variances, and when there is evidence of non-normality. A couple of other people have asked this question, the responses I found have been: ?oneway.test However, that function appears to use the Welch W statistic which,

Dear all a couple of months ago i've found threads regard test that verify AnOVa assumption on homogeneity of variances. Prof. Ripley advice LDA / QDA procedures, many books (and many proprietary programs) advice Hartley's F_max, Cochran's minimum/maximum variance ratio (only balanced experiments), K^2 Bartlett's test, Levene's test. Morton B. Brown and Alan B. Forsythe in a

Hi, do anyone know which statistical software have the Brown-Forsythe Test for differences of numerical continue data groups wich variance heterogenity? not ofr evaluate the homogenity of variances, for evaluated the differences between groups as ANOVA. thanks Jos?? Herrera M??xico _________________________________________________________________ T1msn Search. Todo lo que buscas ahora m??s

> From: Peter Dalgaard BSA <p.dalgaard at biostat.ku.dk> > Date: 01 Sep 2000 09:54:59 +0200 > > Prof Brian D Ripley <ripley at stats.ox.ac.uk> writes: Important omission: specification from Murray Jorgensen The test that I was thinking of basically does an anova on a modified response variable that is the absolute value of the difference between an observation

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

Does oneway.test do what you want? Hope this helps, Matt Wiener -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Sven Hartenstein Sent: Monday, June 21, 2004 3:23 PM To: r-help at stat.math.ethz.ch Subject: [R] Welch-JM-Test or Brown-Forsythe-Test in R? Hi, I want to test mean differences of > 2 groups with

I would appreciate confirmation that the function vcov(model.nlme) gives the var-cov matrix of the fixed effects in an nlme model. Presumably the random-effects var-cov matrix is given by cov(ranef (model.nlme)? Rob Forsyth

In some trial simulation work I need to create batch files that will repeatedly generate pseudoreplicate datasets and then create non- linear mixed effects models using nlme. Inevitably these models sometimes fail to converge but I need the batch file to simply move on to another simulation rather than abort. I am using the try() function as in model<-try((nlme(...))) which handles

After loading the RODBC package version 1.1-7, Ctrl-C changes its behaviour and is quitting R and returning to the (unix-)command prompt on the solaris2.8 platform here. Here's what happened before and after loading RODBC > for (i in 1:10^5) rnorm(10) ^C > library(RODBC) > for (i in 1:10^5) rnorm(10) ^C bash-3.00$ platform sparc-sun-solaris2.8 arch

I have heterogeneous variance in a two-way mixed effects ANOVA, with more than 2 groups in each factor. Is there something like oneway.test or a Brown-Forsythe test that will let me test for differences in means? Thanks! -Keith

Has the Levene test of homogeneity of variance been implemented in any library in R? Thanks, Maurice Haynes National Institute of Child Health and Human Development Child and Family Research Section 6705 Rockledge Drive Bethesda, MD 20892 Voice: 301-496-8180 Fax: 301-496-2766 E-Mail: mh192j at nih.gov

The Brown-Forsyth test for homogeneity of variance is included in the HH package, downloadable from CRAN. library(HH) x <- c(rnorm(1000), rnorm(1000, 0, 1.2)) tmp <- data.frame(x=x, group=rep(c("s1","s1.2"), c(1000,1000))) plot.hov(x ~ group, data=tmp) hov(x ~ group, data=tmp)

Hi folks, I am sitting with a requirement to configure an account for shared use, with access via SSH, and RSA/DSA keys. What I would like to do, and I know it is not foolproof, is log the key presented in order to log on, for audit purposes. The intention is that each user has their own key pair, and the public keys are all stored on the server, as expected. When the key presented is accepted,

I'm having a great deal of trouble replicating x12 ARIMA's F-test used to detect moving seasonality. According to all literature I could find, the test is apparently a 2-way ANOVA with year and month as factors for the SI ratios determined by x12's smoothing algorithm. Note the SI ratio is simply the detrended series. The summary I get from manually running this 2-way ANOVA using the

Dovecot Version 2.0.9 I am having an issue where all vacation messages are being sent to root. Is any one able to advise. Dovecot Log Shows :- Sieve: msgid=< CAMD5TViw0sSigGm8JY5WOv0ROs1UdCJFnvb9vo-RzcNN74E92Q at mail.xxxxxx.com>: sent vacation response to <root> The emails are handed off to dovecot from sendmail using procmail :0 w | $DELIVER The variable $DELIVER is set as

Hello all now that I have finally got CyrusSASL to authenticate.... next up is installing Samba I'm running FreeBSD 5.2.1 and have the options in the ports tree of 2.2.11 and 3.0.6 In my test server intall I used 2.2.8 with success, and it is still running at home on a P166.... as a PDC but here at work it must work for mostly Win98SE machines, plus a couple of Win2000 and XP laptops.

Hi, All! To calculate Levene's Test for Homogeneity of Variance I use R Commander, and this is the output: > levene.test(Dataset$age, Dataset$sex) Levene's Test for Homogeneity of Variance Df F value Pr(>F) group 1 0.8739 0.3567 33 I am not sure what means "Pr(>F)"? Can anyone explain/translate this? Regards, Iurie Malai Department of Psychology and

Hi all, I want to know how to perform the test Breslow-Day test for homogeneity of odds ratios (OR) stratified for svytable. This test is obtained with the following code: epi.2by2 (dat = daty, method = "case.control" conf.level = 0.95, units = 100, homogeneity = "breslow.day", verbose = TRUE) where "daty" is the object type table svytable consider it, but

#### I checked through every 3 factor * 3 loading case. #### While, 4 factor * 3 loading failed. #### the data is 6 factor * 3 loading require(sem); cor18<-read.moments(); 1 .68 1 .60 .58 1 .01 .10 .07 1 .12 .04 .06 .29 1 .06 .06 .01 .35 .24 1 .09 .13 .10 .05 .03 .07 1 .04 .08 .16 .10 .12 .06 .25 1 .06 .09 .02 .02 .09 .16 .29 .36 1 .23 .26 .19 .05 .04 .04 .08 .09 .09 1 .11 .13 .12 .03 .05 .03

I was wondering if somebody could explain why I get different results here: >treats[,2]<-as.factor(treats[,2]) >treats[,5]<-as.factor(treats[,5]) >treats[,4]<-as.factor(treats[,4]) #there are 'c' on more days than I have 'h2o2', where treats[,4] is the day. I only want 'c' that correspond to the same days that I have a 'h2o2' also.