similar to: Post-Hoc tests for Friedman Test?

Dear R users, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance with kruskal.test() function. I am comparing three different groups. The preliminary analysis using the kruskal-wallis-test show significance, but I still don''t know the relationship and the significance level

I followed the threads that enquired about doing post-hoc tests after doing Kruskal testing. It took me to npmc. But npmc is giving an output I do not understand. I noticed a thread entitled "npmc function: 'x' must be atomic" but there never appeared to be a resolution. > npmc(npmcinput) Error in sort(unique.default(x), na.last = TRUE) : 'x' must be atomic

Hi folks, sorry if this has been answered before, I searched long and hard before deciding to make a thread. I'm trying to include multiple variables in a non-parametric analysis (hah!). So far what I've managed to figure out is that the NPMC package from CRAN MIGHT be able to do what I need, but I can't get it to. First I created a dataset as NPMC calls for. > Ind=Individual

Hi, I sent an earlier message concerning this, but perhaps I wasn't clear enough. Up until about a month ago, I downloaded packages by clicking on the filename of the package. Now this action leads me to a directory listing, e.g.: drwxr-xr-x hornik/users 0 2002-03-20 18:00:54 npmc/ -rw-r--r-- hornik/users 314 2002-03-20 11:33:42 npmc/DESCRIPTION -rw-r--r-- hornik/users 202

HI, I am a new user of R and want to analyse some data using npmc. My data have several levels of factor (Site, Year and Season) and several variable (Percentages). I have tried to use npmc but I always get an error message. My data are in a table following this example: Site YEar Season Var1 Var2 .... A 2009 Dry 10 56 B ........ here is the error

Hi there, I am having a problem with package npmc. If I use the included datasets (brain, kronen) everything is fine, but if I try and use my dataset I receive an error message: Error in probval.GenzBretz(algorithm, n, df, lower, upper, infin, corr, : NAs in foreign function call (arg 2) In addition: Warning message: In probval.GenzBretz(algorithm, n, df, lower, upper, infin, corr, : NAs

Hi, I'm having trouble getting the function `npmc' working. I have a 2 column 30 row table called `mydata': > npmc(mydata, df=2, alpha=0.05) Error in sort(unique.default(x), na.last = TRUE) : `x' must be atomic > is.atomic(mydata) [1] TRUE Is there anything I have overlooked? Am I invoking the function correctly? I wasn't able to find any hints in the archives

Dear all, I've discovered the possibility to do the Nemenyi-Damico-Wolfe-Dunn test in the library(coin); oneway_test() With the given example I am unfortunately not able to reproduce the test. What does trafo and contrMat mean? I have a dataframe with 176 elements in 7 classes. It may be a problem, that my model isn't balanced? In Class1 I happen to have 4 elements, while there are 90 in

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

Hi Does anyone know where is the package: npmc (Nonparametric Multiple Comparisons). I found the reference on R Site Search, but not the package itself on CRAN as suggested. Thanks Mauricio

Does anyone know if any R package has a function that will conduct Hollander's test of bivariate symmetry? (Hollander, Biometrika, 1971) Either the exact test or an asymptotic version would be sufficient for my purposes. Thanks. Joe Boyer Statistical Sciences Renaissance Bldg 510, 3233-D Mail Stop RN0320 8-275-3661 cell: (610) 209-8531 [[alternative HTML version deleted]]

Hi, I am using R 2.10.1 and I have a doubt. Do you know how many cases can R handle? I want to use the library npmc but if I have more than 4,500 cases I get an error message. If I use less than 4500 cases I don´t have problems with this library. Is there any way to increase the number of cases in order to use this library. Thanks in advance Julio Flores [[alternative HTML version

Hello, I need nemenyi-test or any other post-hoc test for kruskal-wallis, but I just can't find out how to implement this in R. My data set is nitrite concentrations in four different groups which I intend to compare. The kruskal-wallis-test showed significance, but I still don't know between which groups these significances are. Can anybody help me with this? Thanks

Hi there, I've got a small question : is there any post-hoc test for Kruskal rank sum test integrated in R ? I know that the Nemenyi test is one of the post-hoc that can be used, but there's no (to by knowledge) R function for it. What should I do ? Thanks, Etienne

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

Hello, recently we succeeded in doing a test migration from NT4 to a samba BDC with LDAP. The LDAP directory is now filled with machine, group and user account information. My question: as I have set the smb.conf parameter "ldap passwd sync = Yes", I would have expected that "net rpc vampire" would also set the UNIX password of the LDAP user account entries, i.e. the

Dear fellow R users, Keywords: Kruskal-Wallis, Post-Hoc, pair-wise comparisons, Nemenyi-Damico-Wolfe-Dunn test, coin package, oneway_test I am using the "oneway_test" function in the R package "coin" and I am obtaining results which I cannot believe are accurate. I do not wish to waste anyone's time and so if the following problem is rather trivial, I apologize, however I

Hi list, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance (kruskal.test() function object). I was looking for something like the Dunn Test. I’ve searched the internet but nothing seemed to define a way to it. Do You have any suggestion? Other equivalent test maybe! Thanks in

Dear R Developers, the following CRAN packages do not cleanly pass R CMD check for quite some time now and did not have any updates since the time given. Several attempts by the CRAN admins to contact the package maintainers had no success. norm, 1.0-9, 2002-05-07, WARN sound, 0.6, 2002-08-31, WARN Bhat, 0.9-07, 2003-11-04, WARN HI, 0.1, 2003-11-04, WARN mmlcr, 1.3.2, 2003-11-15, WARN mvnmle,

Hello, I am trying to run a nonparametric comparison of multiple datasets (A-E). After importing my csv file I sorted the variable value by the letter class (representing height along a streambank). a=Z[Letter=="A"] b=Z[Letter=="B"] c=Z[Letter=="C"] d=Z[Letter=="D"] e=Z[Letter=="E"] Next I tested normality and variance assumptions and the