similar to: Nonparametric k-way ANOVA

I am interested in applying a "classification tree" analysis where the response variable is a censored variable (survival data). I've discovered the package 'party' through this page: http://www.statmethods.net/advstats/cart.html. However, as my sample is not very big I would like to apply 'bootstrap' and use 'random forests', but with my censored response

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 all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

Hi all, The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney test to *k* samples. That being the case, the Kruskal-Wallis test with *k*=2 should give an identical p-value to the Mann-Whitney test, should it not? x1<-c(1:5) x2<-c(6,8,9,11) a<-wilcox.test(x1,x2,paired=FALSE) b<-kruskal.test(list(x1,x2),paired=FALSE) a$p.value [1] 0.01587302 b$p.value [1]

Dear Sir, I would like to ask whether there is any tool in R, developed for the function of non parametric Anova, where the non parametric analysis is able to compute the p-value for interaction as well (similar to Anova)? If not, would sir like to suggest any of the other statistical software around which would have this tool? Thank you. LYLing. ?SAVE PAPER! SAVE THE WORLD! - Please do not

For some small sample sizes I would like to exemplify the combinatorics underlying certain nonparametric tests like Mann-Whitney-Wilcoxon, Kruskal-Wallis and Spearman's rank correlation. I have written a function all.perm which delivers all permutations of 1,2,...,n and which works reasonably well. This can be used to generate P(R=r) of Spearman's rank correlation:

Dear all, I run a kruskal wallis test and found significant results. Then, I conducted all pairwise comparisons and found no significant results. Could anyone please give me a hint as to why this happens or redirect me towards a specific web page where I can find more info? (I used alpha=5% and made no bonferroni or other correction for the pairwise comparisons) Thank you   Dr. Iasonas

Dear Sirs, My name is Marcelo Grimaldi and I work for GE Lighting Brazil in Six Sigma Program. In order to accomplish a statistical project I need to generate exact tables for the Kruskal-Wallis statistic ("Three or More Populations Location Test") and I wonder if R could help me. In the past I have heard of generating tables for Wilcoxon statistic using R. Could you help me ? Thank

Dear all Is there any way of doing a Tukey HSD post-hoc test after a Kruskal- Wallis or Friedman rank sum test (in the ctest package)? Thanks in advance, Albertus Dr. Albertus J. Smit Department of Botany University of Cape Town Private Bag Rondebosch 7700 South Africa Tel. +27 21 689 3032

Hi, I was wondering if it was possible to do the "Scheirer-Ray-Hare" extension of the Kruskal-Wallis test using R, or if it was possible to use some other non-parametric test for the following situation: I have continuous data that is grouped by 2 factor variables. I would like a non-parametric test because the group variances are not equal. I would like to look for the effects of

Hi All, What do you consider to be the best book(reference) on nonparametric regression? I am currently reading the book of Kunio Takezawa(2006): "Introduction to nonparametric regression". Is the book of Hardle(1990): "Applied nonparametric regression" better? or maybe another book? This is off topic, but most of the books is using R or S-plus. Thanks Hennie

Hi, I am doing my PhD and I usually use SPSS however now I need to do some multivariate nonparametric tests but SPSS don?t work with this. Recently I was aware of R and I saw that is possible using the MNM pack to perform multivariate nonparametric tests. I am learning step by step how to work in R meanwhile I need to perform the multivariate nonparametric tests for my PhD and I have no idea

Dear UseRs: Recently, I have read an article regarding the association between age and lymph node metastases. http://jco.ascopubs.org/content/27/18/2931.long In statistical analysis, the authors stated "Because a nonlinear relationship between age and lymph node involvement was expected based on existing literature, lymph node involvement was also regressed on age using nonparametric

Hi all, I'd like to compare species richness patterns of two groups with paired observations with an extra continuous fixed effect as a covariate. Normally I would use a standard general mixed effect model for such data, with one group variable and a continuous variable as fixed effects, plus a random effect for the paired observations. However, after making such a model with the lme

Hello! For comparing two non-normally distributed samples, Leech (2002) suggested to report nonparametric effect size indices, such as Vargha & Delaney's A or Cliff's d. I tried to search the R-sites, but could not find related procedures or packages that include nonparametric effect sizes. Thank you for your help! Citation: Leech (2002). A call for greater use of nonparametric

Dear all, Does anybody know how to get more evaluation points in performing Nonparametric analysis of repeated measurements data with "sm" library. The following command gives the estimation for 50 points, by I would like to increase to 100 points But I do not know how to do that. library(sm) provide.data(citrate, options=list(describe=FALSE)) provide.data(dogs,

My interpretation of the relation between 1-way ANOVA and Wilcoxon's test (wilcox.test() in R) is the following. 1-way ANOVA is to test if two or multiple distributions are the same, assuming all the distributions are normal and have equal variances. Wilcoxon's test is to test two distributions are the same without assuming what their distributions are. In this sense, I'm wondering

I am trying to do a Nonparametric Tukey-type multiple comparison post-hoc test to determine which groups are significantly different. I have read the dialogue on this topic from the R-help, and am still not clear why no statistical packages include this test as an option? Is it not an appropriate test to conduct on non-normally distributed data? Is the only option to calculate it by hand

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

Hi, I have seen a discussion in the R-help asking whether nonparametric manova has been implemented in R yet. This discussion is form March 2006 and there seemed to be no package or function implemented at the time. Has this changed? Is there a package that provides nonparametric manova as in McArdle and Anderson (2001) and Anderson (2001) now? Thanks, Daniel ------------------------- cuncta