similar to: minmun p-value for wilcox.test and correlation

Good afternoon Running R2.10.0 on Windows I have a data frame that includes (among much else) a factor (In_2006) and a continuous variable (math_3_4). I would like to find the 2 cases for In_2006 = 0 that are closest to each case where In_2006 = 1. My data looks like In_2006 math_3_4 0 55.1 1 51.6 1 18.1 1 26.6 1 14.1

I have been trying to draw histogram for my manscript and found some strange things that I could not figure out why. Using the same code listed below I have successfully draw histograms for a few figures with fraction labeled on Y axis less than 1 (acturally between 0 to 0.1). But one dataset gives the Y axis label 0 to 5 as fraction. This is not true, as fraction are less than 1, although the

Proposal That a new mailing list be established that pertains exclusively to R documentation. The purpose of the list would be to discuss weak sections of the documentation and establish fixes for those weak spots. Pro If it works, there would be better documentation. It would be an excellent opportunity for newish and/or less technical people to contribute to R. In some respects such people

Hello Running R2.9.2 on Windows XP I am puzzled by the performance of LME in situations where there are missing data. As I understand it, one of the strengths of this sort of model is how well it deals with missing data, yet lme requires nonmissing data. Thus, m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random =

Hi, We could use qqplot to see how two distributions are different from each other. To show better how they are different (departs from the straight line), how is it possible to plot the straight line that goes through them? I am looking for some thing like qqline for qqnorm. I thought of abline but how to determine the slope and intercept? Best wishes, Carol

This was filed as a bug report on the Debian r-base package. It is more properly a bug report on the ctest package in R. The default method for wilcox.test manipulates x and y without checking the class or data.class of these objects. Possible solutions are - create wilcox.test.factor (if appropriate) - check the class and/or data.class of x and y in wilcox.test.default and produce error

Good afternoon Using R 2.9.2 on a machine running Windows XP I have a longitudinal data set, with data on schools and their test scores over a four year period. I have centered year, and run the following m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random = ~I(year-2007.5)|schoolnum, na.action = "na.omit") where

Hi everyone, I am wondering if there exists a stepwise regression function for the Bayesian regression model. I tried googling, but I couldn't find anything. I know "step" function exists for regular stepwise regression, but nothing for Bayes. Thanks -- View this message in context: http://www.nabble.com/Bayesian-regression-stepwise-function--tp26013725p26013725.html Sent from

We've seen the integer overflow problem in ks.test before, easily solved. The help page says x and y must be numeric, so this is user error. I've added tests to the code. Why do people file bug reports without reading the help/man page? On Tue, 14 Jan 2003 bates@stat.wisc.edu wrote: > This was filed as a bug report on the Debian r-base package. It is > more properly a bug

Good morning I just got a new computer with Windows 7. R works fine, but the editor I am used to using "RWinEdt" does not. I did find one blog post on how to get RWinEdt to work in Windows 7, but I could not get those instructions to work either. Is there a patch for RWinEdt? If not, is there another good R editor that works under Windows 7? I tried RSiteSearch with various

Good morning I am learning about NLME and LME4, using Pinheiro and Bates and other materials from Douglas Bates, but I have not seen anything on how to do variable selection sensibly in this type of model. In OLS regression, I frequently use the lasso, but googling did not reveal a method for lasso with mixed models. Most of the material I've seen on these packages is about models with very

hi, when performing a wilcox.test or a wilcox.exact i get results that looks like this: wilcox.exact(x, mu=.5) Exact Wilcoxon signed rank test data: x V = 207, p-value = 0.0006905 alternative hypothesis: true mu is not equal to 0.5 the way i understand the wilcox.test (or wilcox.exact) the V-value represents the summed up ranks of either the positive or negative differences,

Your second issue seems like a more or less unavoidable floating-point computation issue. The paired test operates by computing differences between corresponding values of x and y. It's not impossible to try to detect "almost-ties" (by testing for differences less than, say, sqrt(.Machine$double.eps)), but it's delicate and somewhat subjective/problem-dependent. Example:

Full_Name: David Wooff Version: 1.7.0 OS: i686-pc-linux-gnu Submission from: (NULL) (129.234.4.10) wilcox.test exits with error message when confidence interval required, under some situations. I suspect this occurs when the data contain a zero and for some data lengths only: print(wilcox.test(c(2,1,4,3,6,-5,0),conf.int=T)) fails print(wilcox.test(c(2,1,4,3,6,-5,0,1),conf.int=T)) works

I'm having trouble with the wilcox.test command in R. To demonstrate the anomalous behavior of wilcox.test, consider > wilcox.test(c(1.5,5.5), c(1:10000), exact = F)$p.value [1] 0.01438390 > wilcox.test(c(1.5,5.5), c(1:10000), exact = T)$p.value [1] 6.39808e-07 (this calculation takes noticeably longer). > wilcox.test(c(1.5,5.5), c(1:20000), exact = T)$p.value (R closes/crashes)

Dear R Core, pairwise.wilcox.test does not handle "paired = TRUE" correctly; e.g. set.seed(13) x <- rnorm(20) g <- c(rep(1, 10), rep(2, 10)) wilcox.test(x ~ g)$p.value # 0.075 pairwise.wilcox.test(x, g)$p.value # 0.075, o.k wilcox.test(x ~ g, paired = TRUE)$p.value # 0.105 pairwise.wilcox.test(x, g, paired = TRUE)$p.value # 0.075, wrong The line wilcox.test(xi, xj,

Does anyone know why wilcox.exact gives W-statistic 6 instead of 12 as indicated below. 12 is the rank sum of group 0 of x, which is the linear statistic computed by wilcox_test. y<-c(1,2,3,4,5) x<-c(1,1,0,0,0) (a) wilcox.exact wilcox.exact(y~x) Exact Wilcoxon rank sum test data: y by x W = 6, p-value = 0.2 alternative hypothesis: true mu is not equal to 0 (b) wilcox_test

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hi, i am looking for a way to correct for ties in the wilcoxon signed rank test -> e.g. wilcox.test(x,mu=.5) one way i have heard of is to look up the p value in a table that has been produced by Buck (1975). obviously i need to know the T-value to do that -> how do i get the T-value from the wilcox.test() function. is there any other (already implemented) way to correct for ties in

Hi, I am very confused with constructing the wilcox.test in R. I have two populations 'original' and 'test'. I want to know if the 'test' is generally 'lower' than original. I use alpha of 0.05. So do I write the function as wilcox.test(original, test, alternative="l")? or wlcox.test(original, test, alternative = "g")? or wilcox.test(test,