similar to: Equivalence test and factors

We are getting some pushback from our SA group regarding root having ssh user equivalence on the cluster where we run OCFS2. Is it required to have the ssh user equivalence setup for the root user when running OCFS2 ? Thanks in advance, Reid Reid McKinley ******************************************************************************************** This message, including any

Hello, I am analysing several samples whose sizes are from 9 to 110. I would like to test their distribution with R, whether they are normal or not. I wonder which test for normality from R should I use . Thank you for help. Samuel Samuel BERTRAND Doctorant Laboratoire de Biomecanique LBM - ENSAM - CNRS UMR 8005 151, bd de l'Hopital 75013 PARIS Tel. +33 (0) 1 44 24 64 53 Fax +33 (0) 1

Hi, I use ks.test or lillie.test to verify a normal distribution. It's performed for a group My users use SigmaStat software and a One Way ANOVA on several groups In the result page there is a probability value to determine if Normality test is failed or passed So, how can i retrieve this probability value on several groups? Is there another function in R to verify normality on several

Dear All, Apologies if you have a seen a question like this from me before. I am hoping that if I re-word my question more carefully someone may be able to offer more help than the last time I asked something similar. I am using R 2.9.2 and Windows XP. I am trying to determine if there is a statistically significant difference between two c-statistics (or equivalently D statistics). In Stata

Hi! is there a way in R to check whether the outcome of two different experiments is statistically distinguishable or indistinguishable? More preciously, I used the wilcoxon test to determine the differences between controls and treated subjects for two different experiments. Now I would like to check whether the two lists of analytes obtained are statistically distinguishable or

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, is it possible to do an equivalence test on paired quantitative datas in R? Is there a way to calculate sample size for such tests? I've tried to find some documentation on that subject but I was unsuccessfull. I'll be happy with any links on equivalence test. If such a test does'nt exist in R, i'll do it manually if I find a

Hi Dears, When I introduce an interaciton in a piecewise model I obtain some quite unusual results. If that would't take u such a problem I'd really appreciate an advise from you. I've reproduced an example below... Many thanks x<-rnorm(1000) y<-exp(-x)+rnorm(1000) plot(x,y) abline(v=-1,col=2,lty=2) mod<-lm(y~x+x*(x>-1)) summary(mod) yy<-predict(mod)

Given an object o of ElemType in an instance of EquivalenceClasses, I need to get a list of all members of the equivalence class that o is in. For various reasons, it is easiest if I could get an EquivalenceClasses::iterator that I can pass to member_begin and member_end. So naturally, I did something like this (pseudo-C++): EquivalenceClasses::iterator i = equiv.findValue(o);

Simple example: # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start, method="class", data=kyphosis) Now I would like to know how can I measure the "importance" of each of my three explanatory variables (Age, Number, Start) in the model? If this was a regression model, I could have looked at p values from the

Hi, I've got one silly question for evening. I don't know is this reasonable, but can test with two the most extreme proportions from the samples could be good enough evidence for testing equivalence, or should I have to look for something else...? -- Mi³ego dnia [[alternative HTML version deleted]]

This code executes just fine, and leaves the SIP peer's mailbox setting from sip.conf in variable target. exten => 1,1,Set(target=${CHANNEL:4}-) exten => 1,n,Set(target=${SIPPEER(${CUT(target,,1)}:mailbox}) exten => 1,n,VoiceMailMain(${target}) However, every time it runs I get an error in the CLI as follows WARNING[5629]: pbx.c:1366 ast_func_read: Can't

Dear R-Community! For example I have a study with 4 treatment groups (10 subjects per group) and 4 visits. Additionally, the gender is taken into account. I think - and hope this is a goog idea (!) - this data can be analysed using lme as below. In a balanced design everything is fine, but in an unbalanced design there are differences depending on fitting y~visit*treat*gender or

Anton, I didn't know that EQUIVALENCE is the only unsupported major Fortran feature, as this bug says. Can you give me an update on the status of the Fortran front-end and what the near-term goals are? I am getting more requests from academics doing HPC compilers and it would be useful to know where Fortran support stands. Other llvmdev'ers may be interested too. Thanks,

RoR Equivalence of TSQL Stored Procedures and User defined functions As I browsed through the tutorials and online eBook ?Programming Ruby?, I have not come across the terms ?Stored Procedures? or ?User-defined functions? as I know them in SQL 2000. However, the online documentations in MySQL 5.0 show that Stored Procedures and User-defined functions are supported in MySQL 5.0. I wonder what

Hi, I have an unbalanced dataset on which I would like to perform a one-way anova test using R (aov). According to Wannacott and Wannacott (1990) p. 333, one-way anova with unbalanced data is possible with a few modifications in the anova-calculations. The modified anova calculations should take into account different sample sizes and a modified definition of the average. I was wondering if the

Sorry for the repost, but I've really been looking, and can't find any syntax direction on this issue... Just browsing the documentation, and searching the list came up short... I have some unbalanced data and was wondering if, in a "0" v "1" classification forest, some combo of these options might yield better predictions when the proportion of one class is low (less

"classwt" in the current version of the randomForest package doesn't work too well. (It's what was in version 3.x of the original Fortran code by Breiman and Cutler, not the one in the new Fortran code.) I'd advise against using it. "sampsize" and "strata" can be use in conjunction. If "strata" is not specified, the class labels will be used.

Vikram, > I didn't know that EQUIVALENCE is the only unsupported major Fortran > feature, as this bug says. Can you give me an update on the status of > the Fortran front-end and what the near-term goals are? Ok. I was going to post something soon after 2.2 release, but let's do it now. LLVM 2.2 will contain (as a part of llvm-gcc 4.2) a port of gfortran compiler to the LLVM

Dear list members, I want to use a GLM with an unbalanced factor and continuous variables. My factor F has 12 unbalanced levels:

I have a three-way unbalanced ANOVA that I need to calculate (fixed effects plus interactions, no random effects). But word has it that aov() is good only for balanced designs. I have seen a number of different recommendations for working with unbalanced designs, but they seem to differ widely (car, nlme, lme4, etc.). So I would like to know what is the best or most usual way to go about working