search for: homogenized

I am testing the homogeneity of variances via bartlett.test and fligner.test. Using the following example, how should I interpret the p-value in order to 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 =

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

Dear r-helpers, Prior to analysis of variance, I ran the Boxcox function (MASS library) to find the best power transformation of my data. However, reading the Boxcox help file, I cannot figure out if this function (through its associated log-likelihood function) corrects for * normality only * or if it also induces * homogeneity of variances *. I found in Biometry (Sokal and Rohlf, p. 419)

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

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me

Dear R-users, We expect to create N homogenic groups of n features from an experimentation including N*n mesures. The aim of this is to prevent from group effects. How to do that with R functionalities. Does anyone know any methodes enabling this ? Best regards. Alexandre MENICACCI Bioinformatics - FOURNIER PHARMA 50, rue de Dijon - 21121 Daix - FRANCE a.menicacci at fr.fournierpharma.com t??l

I want to do a non homogeneous poisson process model in R. Any advice, or know of places where i can get some, ive googled it but nothing came up relating to R. -- View this message in context: http://old.nabble.com/non-homogeneous-poisson-process-tp26378037p26378037.html Sent from the R help mailing list archive at Nabble.com.

Hello dear R-help mailing list, A friend of mine teaches a regression and experimental design course and asked me the following question. She is trying to find a way to display the "homogeneous groups" (after performing tukey test on an aov object). here's an example for what she means by "homogeneous groups": She did one way anova and got these results for tukey test:

Hello, I'd like to upstream our work over the time which the community would benefit from. This is a part of effort toward minimizing code size presented in here <https://llvm.org/devmtg/2020-02-23/slides/Kyungwoo-GlobalMachineOutlinerForThinLTO.pdf>. In particular, this RFC is about optimizing prolog and epilog for size. *Homogeneous Prolog and Epilog for Size Optimization, D76570

Dear all, I have been trying to find a function to calculate the Breslow-Day test for homogeneity of the odds ratio in R. I know the test can be preformed in SAS but i was wondering if anyone could help me to perform this in r. In addition i have the fullrefman file to search for functions in the basic R packages, does anyone have any suggestions of an efficient way of searching for

I was playing in Glade tonight with couple of GUI ideas for the vorbis comment editor. I've attached the glade file. A few notes: On the user-friendly version, we might want an "Advanced" tab that would pop up the user-hostile version to edit "non-standard" comment tags. I'm just not sure how to do that in a way that won't scare the non-technical. We need to

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Dear all I would like to show my audience that some variables are homogenous inside groups but different outside. I can use by with summary for all variables by(iris[,1:4], iris$Species, summary) what can be quite messy in case of more than few variables and about 8 groups or densityplot for one variable densityplot(~Petal.Length | Species, iris) I have two questions: 1. Is there

Dear Group Members, Forgive me if I am a little bit out of subject. I am looking for a good way to test the homogeneity of two variance-covariance matrices using R, prior to a Hotelling T test. Youll probably tell me that it is better to use a robust version of T, but I have no precise idea of the statistical behaviour of my variables, because they are parameters from the harmonics of

Hi Vedant, Thanks for your interest and comment. Size-optimization improves page-faults and a start-up time for a large application, which this enabling also followed. Even though I didn't see a large regression/complaint on a CPU-bound case, which is not a typical case for mobile workload, I wanted to be precautious of enabling it by default. However, as with default outlining case, I

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

Breslow-Day test A statistical test for the homogeneity of odds ratios. Homogeneity In <javascript:void(0);> systematic reviews homogeneity refers to the degree to which the results of studies included in a review are similar. "Clinical homogeneity" means that, in studies included in a review, the participants, interventions and outcome measures are similar or comparable.

Hello I am testing for the homogeneity of clusters of (yearly) seasonal data using the rao.test from the circular package. I can't find anywhere (including the Cran pages) which specifically mentions the null hypothesis for this test. Playing around with it, for example using say the toy code beneath it would seem that the null is that the data sets tested are not homogenous, which is fine

Hello all, I'm running very simple regression but face a problem of non-homogeneity of variance, but with a decreasing variance with increasing mean...I do not know how to deal with that. this relationship doesn't seem to be strong, but it's my first time to see something like that, and would like to know what to do if one day it becomes stronger. I tested just for fun some

I partly answered my question since independence_test() function in coin package apparently do Cochran-Armitage trend test just like Eric Lecoutre's function tabletrend() - slightly modified here: > independence_test(pheno ~ geno, data = dat2, teststat = "quad", scores = list(geno = c(0, 1, 2))) Asymptotic General Independence Test data: pheno by groups 1 < 2