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Dear all, I have another question about fisher.test: Is there any way to save the resulting p-value in a matrix or file after a loop as below? for (i in 1:42) { # testing difference in income(pinc) between people in # (with in1=1) and out (with in1=0) of the program for # group i fisher.test(m$pinc[m$group==i], m$in1[m$group==i], workspace=40000000, hybrid=F)} When I run this loop, there is no

Dear all, I have another question about fisher.test: Is there any way to save the resulting p-value in a matrix or file after a loop as below? for (i in 1:42) { # testing difference in income(pinc) between people in # (with in1=1) and out (with in1=0) of the program for # group i fisher.test(m$pinc[m$group==i], m$in1[m$group==i], workspace=40000000, hybrid=F)} When I run this loop, there is no

[In future, please press reply all as there might be others in the mailing list who can help you] Without a (short) reproducible example, it would be difficult to say. BTW, I think you have mistyped the error/warning message. Does it actually say "cannot compute _correct_ p-value" or "cannot compute _exact_ p-value". See example below. > wilcox.test( 1:3, 1:10 )

Hi, I have a simple task I can't figure out. I'd like to take some measurements I made, e.g.: year (y-axis) 1 2 3 4 5 6 counts (x-axis) 10 10 20 30 40 50 And then, make a barplot with the x-axis ticks (representing the borders between years) between the bars. However, barplot seems to force you to make the x-axis arbitrary categories. I want it to be continuous (as in a

The hybrid feature in fisher.test looks to me like an excellent way to analyze my two-way tables. The only problem is that it does not seem to be implemented. Am I right about this? An example is pasted below. I note that I get the warning message only when I shouldn't: for a 2x2 table hybrid seems to be ignored without warning. In no case does fisher.test seem to be checking Cochran

Hi folks, Forgive me if this question is a trivial issue. I was doing a series of Fishers' exact test using the fisher.test function in stats package. Since the counts I have were quite large (c(64, 3070, 2868, 4961135)), R suggested me to use *other algorithms* for the test which can be specified through the 'control' argument of the fisher.test function as I understood. But where

Full_Name: Martha Nason Version: 2.0.1 OS: Windows XP Submission from: (NULL) (137.187.154.154) I am running simulations using fisher's test on 2 x c tables and a very small p.value from fisher's test (<2.2e-16) is returned as a negative number. Code follows. > set.seed(0) > nreps.outer <-7 > pvalue.fisher <- rep(NA,nreps.outer) > > population1 <- c(

I want to ascertain the basis of the table ranking, i.e. the meaning of "extreme", in Fisher's Exact Test as implemented in 'fisher.test', when applied to RxC tables which are larger than 2x2. One can summarise a strategy for the test as 1) For each table compatible with the margins of the observed table, compute the probability of this table conditional on the

Hi, > ----- Original Message ----- >>> ----- Original Message ----- >>>> Hi all, >>>> My recent commit r187027 fixed a simple oversight of forgetting >>>> to >>>> check for __ppc__ (only checking __powerpc__), which broke my >>>> powerpc-apple-darwin8 stage1 tests, since the system gcc only >>>> provided

fisher.test(matrix(c(1,20,246,6873),2),hybrid=F) Error in if (f(lower, ...) * f(upper, ...) >= 0) stop("f() values at end points not of opposite sign") : missing value where logical needed Thomas Lumley Assistant Professor, Biostatistics University of Washington, Seattle -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list --

Dear friends, My dataset have many zeros, so i must use fisher exact test . Unfortunately, the fisher.test(stats) function fail to do it. Anybody knows how to do the fisher exact test with many zeros in the dataset? My dataset is: a<-matrix(c(0,1,0,0,0,0,1,0,1,0,0,0,0,1,0,1,1,0,2,1,5,1,1,6,4,4,1,17,2,8,5,7,1,1,24,3,6,1,1,3,2,16,7,4,0,2,4,0,17,0,1,0,0,0,1,2),nrow=8,byrow=TRUE) data.frame(a)

I have two vectors (a and b) with counts of animals and wanted to calculate fisher's alpha: library(vegan) a <- c(2043, 1258, 52, 1867, 107, 1624, 2, 157, 210, 402, 5, 107, 267, 2, 13683) b <- c(2043, 1258, 52, 1867, 107, 1624, 2, 157, 210, 402, 5, 107, 267, 2, 3000) fisher.alpha(a) fisher.alpha(b) fisher.alpha(a) gave the following warnings: > fisher.alpha(a) [1] 1.572964

Hi, For anyone who might be interested, I've thrown together a little page to track my builds of llvm and clang, both release 3.0 and svn-trunk, on powerpc-darwin8. http://www.csl.cornell.edu/~fang/sw/llvm/ I'll update the list of logs each time I svn-update and build. It's nowhere as nice as a real buildbot page, but it's better than nothing. 3.0 still has over 20 test

> ----- Original Message ----- >> Hi all, >> My recent commit r187027 fixed a simple oversight of forgetting to >> check for __ppc__ (only checking __powerpc__), which broke my >> powerpc-apple-darwin8 stage1 tests, since the system gcc only >> provided >> __ppc__. I was wondering if this justifies using simpler macros like >> >> #define

----- Original Message ----- > > ----- Original Message ----- > >> Hi all, > >> My recent commit r187027 fixed a simple oversight of forgetting > >> to > >> check for __ppc__ (only checking __powerpc__), which broke my > >> powerpc-apple-darwin8 stage1 tests, since the system gcc only > >> provided > >> __ppc__. I was

Data from Fisher's paper: Confidence Limits for a Cross-Product Ratio. > y col1 col2 [1,] 10 3 [2,] 2 15 fisher.test(y) Fisher's Exact Test for Count Data data: y p-value = 0.0005367 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 2.753438 300.682787 sample estimates: odds ratio 21.30533 The crude odds

Hi, Thanks for the quick reply again. > On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >> Hi, >> >> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >> have the following test results to share. >> Summary below, full log at: >>

18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > Hi, >          For anyone who might be interested, I've thrown together a little > page to track my builds of llvm and clang, both release 3.0 and > svn-trunk, on powerpc-darwin8. > > http://www.csl.cornell.edu/~fang/sw/llvm/ > > I'll update the list of logs each time I svn-update and

Suppose we have the following data set: Men Women Dieting 10 30 Non-dieting 5 60 If I run the Fisher exact test in R then what does alternative = greater (or less) imply? For example: mat = matrix(c(10,5,30,60), 2,2) fisher.test(mat,alternative ="greater") I get the p-value = 0.01588 and odds ratio = 3.943534. Also, when I flip the rows of

On Wed, Jan 18, 2012 at 10:51:38PM +0400, Konstantin Tokarev wrote: > > > 18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > > Hi, > > ?????????For anyone who might be interested, I've thrown together a little > > page to track my builds of llvm and clang, both release 3.0 and > > svn-trunk, on powerpc-darwin8. > > > >