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Full_Name: Karel Zvara Version: 1.8.1 OS: MS Winows 2000 Submission from: (NULL) (195.113.30.163) The test statistics of the fligner.test (ctest package) depends on the order of cases: > fligner.test(count~spray,data=InsectSprays) Fligner-Killeen test for homogeneity of variances data: count by spray Fligner-Killeen:med chi-squared = 14.4828, df = 5, p-value = 0.01282 > fligner.test(count~spray,data=InsectSprays[order(InsectSprays$count),]) Fligner-Killeen test for homogeneity of variances data: count by spray Fligner-Kil...

....3 I would like to separate dT in the 32 samples (4x4x2), and test if the variance of each sample is equal to the other 31 samples. I tried using fligner.test and bartlett.test, but either test seems to only work for one factor: > fligner.test( dT ~ Topology + Drift + lambda) Fligner-Killeen test of homogeneity of variances data: dT by Topology by Drift by lambda Fligner-Killeen:med chi-squared = 15.4343, df = 2, p-value = 0.0004451 > fligner.test( dT ~ Topology ) Fligner-Killeen test of homogeneity of variances data: dT by Topology Fligner-Killeen:med chi-squared = 15...

...in the 32 samples (4x4x2), and test if the > variance of each sample is equal to the other 31 samples. > I tried using fligner.test and bartlett.test, but either test seems to > only work for one factor: > > > fligner.test( dT ~ Topology + Drift + lambda) > > Fligner-Killeen test of homogeneity of variances > > data: dT by Topology by Drift by lambda > Fligner-Killeen:med chi-squared = 15.4343, df = 2, p-value = 0.0004451 > > > fligner.test( dT ~ Topology ) > > Fligner-Killeen test of homogeneity of variances > > data: dT by Topo...

I've made fligner test with the same data, changing the orders of the variables, and this what i get > fligner.test(rojos~edadysexo*zona*ano*estacion) Fligner-Killeen test of homogeneity of variances data: rojos by edadysexo by zona by ano by estacion Fligner-Killeen:med chi-squared = 15.7651, df = 2, p-value = 0.0003773 > fligner.test(rojos~ano*edadysexo*zona*estacion) Fligner-Killeen test of homogeneity of variances data: rojos by ano by edad...

Hello, I investigate survival until the following year (0,1) and I wish to test if the variance in survival for two or more groups are significantly different from each other. I read that the Fligner-Killeen test is a non-parametric test which is very robust against departures from normality but is it correct (valuable technique for publication) to use it on binary data? In other words, can I use fligner.test(survival~categorical_predictor,data=mydata) when survival is binary (0,1)? Best regard...

...ine.mourocq at uzh.ch> wrote: > > Hello, > > > > I investigate survival until the following year (0,1) and I wish to test if > the variance in survival for two or more groups are significantly different > from each other. > > > > I read that the Fligner-Killeen test is a non-parametric test which is very > robust against departures from normality but is it correct (valuable > technique for publication) to use it on binary data? > > > > In other words, can I use > fligner.test(survival~categorical_predictor,data=mydata) when surviva...

...accept or reject the null hypothesis ? set.seed(5) x <- rnorm(20) bartlett.test(x, rep(1:5, each=4)) Bartlett test of homogeneity of variances data: x and rep(1:5, each = 4) Bartlett's K-squared = 1.7709, df = 4, p-value = 0.7778 fligner.test(x, rep(1:5, each=4)) Fligner-Killeen test of homogeneity of variances data: x and rep(1:5, each = 4) Fligner-Killeen:med chi-squared = 1.0819, df = 4, p-value = 0.8971

> 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

Can anybody tell me if there is an R implementation of the Fligner-Policello robust rank test? Thanks, Elisabetta

Hello, I notice that when I do Levene's test to test equality of variances across levels of a factor, I get different answers in R and SPSS 16. e.g.: For the chickwts data, in R, levene.test(weight, feed) gives F=0.7493, p=0.5896. SPSS 16 gives F=0.987, p=0.432 Why this difference? Which one should I believe? (I would like to believe R :) Ravi -- View this message in context:

Hi All, is there Levene' test in R ? If not ,Could you give me some advice about Levene test with R? Thanks a lot! I am waiting for yours.

I have a bunch of benchmark measurements that look something like this: sample.1 0.0000066660 0.0000062500 0.0000058330 0.0000058330 0.0000058330 sample.2 0.0000058330 0.0000058330 0.0000058330 0.0000058330 0.0000058330 sample.3 0.0000062500 0.0000062500 0.0000070830 0.0000062500 0.0000066660 i.e each measurement take on one of a set of values. The set values isn't fixed, but

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

...in the 32 samples (4x4x2), and test if the > variance of each sample is equal to the other 31 samples. > I tried using fligner.test and bartlett.test, but either test seems to > only work for one factor: > > > fligner.test( dT ~ Topology + Drift + lambda) > > Fligner-Killeen test of homogeneity of variances > > data: dT by Topology by Drift by lambda > Fligner-Killeen:med chi-squared = 15.4343, df = 2, p-value = 0.0004451 > > > fligner.test( dT ~ Topology ) > > Fligner-Killeen test of homogeneity of variances > > data: dT by Topo...