similar to: Low level algorithm conrol in Fisher's exact test

Hello, I'm using R to apply Fishers exact test to a whole pile of contingency tables, and I've run into the bug shown below. regards, Francis -- > dat1 = matrix(c(0,1,0,1,0,0,1,0,0,0,1,0,1,0,0,1,0,0,0,1,0,1,0,0,1,0,0,0,0, 1,1,0,0,1,0,0,1,0,0,1,0,0,3,0,0,2,0,0,1,0,0,0,1,0,0,2,0,0, 2,0,0,1,0,1,0,0,3,0,0,2,0,0,0,1,0,5,0,0,0,1,0,1,0,0), nrow=3) >

This is a bad bug as reported by Robin Hankin, it is still in "R-patched" ... ##- From: Robin Hankin <r.hankin@auckland.ac.nz> ##- To: r-help@stat.math.ethz.ch ##- Subject: [R] possum sleeping: thanks and fisher.test() FEXACT error ##- Date: Thu, 13 Jun 2002 16:46:26 +1200 ## ..... ## Example slighlty modified (MM) d4 <- matrix(c(0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 0, 0, 0,

Hi, I have recently installed version 2.4.1 of R and also installed SciViews-R 0.8.9. It worked fine. Then I installed the Rcmdr 1.2-7 from CRAN . However the 'R commander menu' in the dockable panel does not work. If I start Rcmdr in R without SciViews, it works perfectly. Is there any way that I can use Rcmdr with SciViews? Many thanks in advanve. Kihwang

I have a matrix with 2 columns and I want to do fishers exact test for these with the totals for each row being 100 say. The data has the form: 23 12 32 21 12 2 and these represents the tables: 23 12 77 88 32 21 78 79 12 2 88 98 How do I use apply to speed up aclculation of the fisher.exact test? -- Thanks, Jim. [[alternative HTML version deleted]]

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

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

Hello, I have an error message that doesn't seem to make sense in that having read the R documentation I was under the impression that R was able to grab as much memory as it needed, and has been able to do so for some time, so the advice given below about increasing the size of the workspace is redundant. If I'm right, does anyone have a solution to the problem of the size of

Timothy, I believe you are mistaken. Fisher's exact test give the correct answer even in the face of small expected values for the cell counts. Pearson's Chi-square approximates Fisher's exact test and can give the wrong answer when expected cell counts are low. Chi-square was developed because it is computationally "simple". Fisher's exact test, particularly with tables

Hi, I'm trying to run Fisher's Exact test on the data below, but I'm not sure how interpret the data shown. Can someone tell me what this is saying? Looking at the numbers it should be that there's no significant difference between the HDL and LDL, but a p-value of 1 seems high. Is the low value in the LDL unbound making the test unstable and should I be using an alternative? Best

I have a matrix say, 1 4 23 30 and I want to find the previously attainable fisher's exact test p-value. Is there a way to do this in R? -- Thanks, Jim. [[alternative HTML version deleted]]

I posted this last night but I think I figured out the problem. I checked on the underlying equation for the Fisher Exact Test for tables greater than 2X2. It looks like I have an insane amount of factorials to be multiplied. Is that problem? Is it an overflow issue? Jeff Last night’s post: I just a ran a fisher.test on a 9x5 table and received the following message

Hi, I have a table of observed counts for various genetic markers. Instead of doing Fisher's exact test for each marker one at a time and recording the P value manually, is there a script to go through the whole list and generate the P value column automatically? An example of my data: Counts_CHB and Counts_AA are the observed counts for one allele. 2N_CHB and 2N_AA are the total number

Is anyone aware of a fast way of doing fisher's exact test for a series of 2 x 2 tables in R? The fisher.test is really slow if n1=1000 and n2 = 1000. -- Thanks, Jim. [[alternative HTML version deleted]]

Hi, I'm try to compute the minimum sample size needed to have at least an 80% of power, with alpha=0.05. The problem is that empirical proportions are really small: 0.00154 in one case and 0.00234. These are the estimated failure proportion of two medical treatments. Thomas and Conlon (1992) suggested Fisher's exact test and proposed a computational method, which according to their table

Hello R help members. I came across today with an article on Barnard's exact test (http://www.cytel.com/Papers/twobinomials.pdf), that is supposed to give a more powerful fisher.test - Because it doesn't assume that we know the row and column totals are in advance. Any pointers to such a function ? Thanks, Tal -- ---------------------------------------------- My contact information:

Hi I was wondering whether anyone can help me with this problem....it's been driving me nuts, I've been trying to figure it out for months and months without success!! Basically I have a group of participants who attended 2 experimental sessions a few months apart. I took measures of the way they approach two tasks at Time 1 and the same two tasks at Time 2. I have categorical data (a

Hi, R-help, I have a group of data from RNA-seq want to be analyzed by Fisher's exact test in R. I want to compare the significant difference of about 30,0000 individuals in two different samples, and I have no idea how to use R, so could you please give me some suggestions or the scripts for Fisher's exact test? Thank you very much. Best, Guanfeng Wang [[alternative HTML version

Hi! I am Marta Colombo, student in Mathematical Engineering at "Politecnico di Milano". For my master degree thesis I have to analyze some categorical data. My dataset is composed by 327 individuals and 16 variables. I am using Fisher exact test to test independence on IxJ contingency tables, but I have a problem with one variable. R gives me this error message: FEXACT error 7.

Dear all, I’m having an awkward problem in R. When I write the command Fisher.test(school.data,workspace=2e+07), where school.data is the matrix corresponding to the data set, I get the error message: FEXACT error 7. LDSTP is too small for this problem. Try increasing the size of the workspace. Increasing the workspace: Fisher.test(school.data,workspace=1e+10), I

Appology in advance if this has been asked and answered. I am getting different answers using Fisher's exact test in the package ctest. For example: x_cbind(c(8, 22), c(31, 29)) fisher.test(x) Fisher's Exact Test for Count Data data: x p-value = 0.04024 alternative hypothesis: two.sided However, in SAS or other packages on the net the answer I get is p-value= 0.02664. Is this