similar to: Performing a non parametric Friedman Test

Dear all, I am conducting a full factorial analysis. I have one factor consisting in algorithms, which I consider my treatments, and another factor made of the problems I want to solve. For each problem I obtain a response variable which is stochastic. I replicate the measure of this response value 10 times. When I apply ANOVA the assumptions do not hold, hence I must rely on non parametric

I am using the normtemp data set in UsingR package. I want to store all normtemp[,1] from 1 to 65 as x and normtemp[,1] from 66to 130 as y. How do I write code to do that from here: > data(normtemp) -- View this message in context: http://r.789695.n4.nabble.com/Using-a-for-loop-tp3896903p3896903.html Sent from the R help mailing list archive at Nabble.com.

We need a two-way non-parametric ANOVA in order to analysis properly some ecological data, do you know any reference in R? or how to do it? Thank you very much All the best diana -- View this message in context: http://www.nabble.com/Two-way-non-parametric-ANOVA--tp15039308p15039308.html Sent from the R help mailing list archive at Nabble.com.

Please forgive a stats question. I have to sets of data (unpaired) measured on an ordinal scale. I want to test to see if the two sets are different (i.e. do they have the same location): set1: 1,3,2,2,4,3,3,2,2 set: 4,4,4,3,3,5,4,4 What is the most appropriate non-parametric test to test location? Thanks, John Confidentiality Statement: This email message, including any attachments, is

I have to start by saying that I am new to R, so I might miss something crucial here. It seems to me that the results of friedman.test and ks.test are "wrong". Now, obviously, the first thing which crossed my mind was "it can't be, this is a package used by so many, someone should have observed", but I can't figure out what it might be. Problem: let's start with

I am trying to apply this technique (M.J Anderson 2001) to a dataset of aquatic insect abundances. There is a sample in the unrestored and restored segement of a stream for every time period. I would like to compare the centroids of the distance matrices for the treatments up (unrestored) and dn (restored) to see if there is a difference in insect communities between the treatments. I will not

Dear all, I'm using friedman rank test in R. Need to know how to calculate rank sum in friedman test (R options to get rank sum in friedman test). Kindly help me. With regards jeevitesh

Hi, I would need to extend the Friedman test to a replicated design. Currently the function: friedman.test(y, ...) only works for unreplicated designs. I found in Conover 1999 "Practical Nonparamteric statistics" an extension of the formula to my case. Nevertheless, other sources, like Sheskin 2000 "Parametric and Nonparametric statistical Procedures" and Daniel 1990

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the code further below does. After the

I am new to R. I'm using the function GAM and wanted to get standard errors and p-values for the parametric terms (I fitted a semi-parametric models). Using the function anova() on the object from GAM, I only get p-values for the nonparametric terms. Does anyone know if and how to get standard errors for the parametric terms? Thanks. Jean G. Orelien

Hi, I am trying to estimate the sample size needed for the comparison of two groups on a certain measurement, given some previous data at hand. I find that the data collected does not follow a normal distribution, so I would like to use a non-parametric option for sample size calculation. I found the pwr package but I don't think it has this option and on the internet found that

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.)

Can anyone suggest a good non-parametric test, and an R implementation of the test, that allows for two or more factors? Wilcoxon signed rank allows for only one. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of Maryland School of Medicine Division of

Hi * i'm trying to do my statistical analysis with R (on a debianGNULinux) i've installed R and now i'll try to import my data from .xls Where to search for non parametric test in R ? I'm studing neurons velocity and i've to check if after the perfusion with a factor x the velocity changes but as my variable is not normally ditributed i've to try with non parametric

Hello, I am trying to test for non-linearity in a set of non-parametric data. Furthermore, I would like to do so in a multi-variate model. Frankly, I don't even know if this is possible, and if it is possible, I don't know if it is implemented in an R package. Any advice would greatly appreciated. Thank you! Charlie -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Charles G.

Hi I have data from an experiment that used a repeated-measures factorial 2x2 design (i.e. each participant contributed data to both levels of both factors). I need a non-parametric version of the repeated-measures factorial ANOVA to analyse the data. SPSS only has non-parametric tests for one-way ANOVAs but I have been told that the test I need can be implemented using the R software.

Dear all, I fitted a non-parametric model using GAM function in R. i.e., gam(y~s(x1)+s(x2)) #where s() is the smooth function Then I obtained the coefficients(a and b) for the non-parametric terms. i.e., y=a*s(x1)+b*s(x2) Now if I want to use this estimated model to do optimization or sensitivity analysis, I am not sure how to incorporate the smooth function since s() may not

Hello R, I am looking for non-parametric simulation in IRT. Is there any IRT package that does non-parametric simulation? helen L [[alternative HTML version deleted]]

Hi everybody! I'm trying to plot a parametric curve (three dimensions) using R but I didn't obtain good results. Somebody have already done something like that? Please help me! Talita Perciano Costa Leite Graduanda em Ci??ncia da Computa????o Universidade Federal de Alagoas - UFAL Departamento de Tecnologia da Informa????o - TCI Constru????o de Conhecimento por Agrupamento de Dados -

Dear all, Is there a way to plot / calculate pointwise confidence bands or interval values for a non parametric regression like sm.regression? Thank you in advance. Regards, Martin