similar to: anova.glm gets test="Chisq" wrong (PR#2294)

The Chisquare test is based upon a normal approx of the (essentially) binomial distribution for the data in question. Small EXPECTED (not observed) values (<5) suggest a asymetric distribution and potential errors in inferential conclusions. The alternative is the exact test, which calculates the exact probabilities of the observed distribution, or a more extreme one, given the constraining

Dear all, I have a question about the chisq.test command. As an option one can chose the computation of p-values by Monte-Carlo simulation (simulate.p.value=T). Is there any documentation available how this calculations are done and how this simulation based test behaves in small samples? Thanks Klaus Abberger University of Konstanz, Germany [[alternate HTML version deleted]]

The chisq.test contains following code: STATISTIC <- sum(sort((x - E)^2/E, decreasing = TRUE)) However, based on book Accuracy and stability of numerical algorithms <http://ftp.demec.ufpr.br/CFD/bibliografia/Higham_2002_Accuracy%20and%20Stability%20of%20Numerical%20Algorithms.pdf> Table 4.1 on page 89, it is better to sort the data in increasing order than in decreasing order, when the

chisq.test with simulate.p.value=TRUE uses the Patefield algorithm, this is not documented, and the original reference is not given, as it ought to be. The reference is: Patefield,W. M. (1981) An efficient method of generating r * c tables with given row and column totals (algorithm AS 159). Applied Statistics 30, 91-97. Kjetil Halvorsen

Full_Name: Tao Shi Version: 1.7.0 OS: Windows XP Professional Submission from: (NULL) (149.142.163.65) > x [,1] [,2] [1,] 149 151 [2,] 1 8 > c2x<-chisq.test(x, simulate.p.value=T, B=100000)$p.value > for(i in (1:20)){c2x<-c(c2x,chisq.test(x, simulate.p.value=T,B=100000)$p.value)} > c2tx<-chisq.test(t(x), simulate.p.value=T, B=100000)$p.value > for(i in

>>>>> dmurdoch writes: >> Date: Wed, 16 Jul 2003 01:27:25 +0200 (MET DST) >> From: shitao@ucla.edu >>> x >> [,1] [,2] >> [1,] 149 151 >> [2,] 1 8 >>> c2x<-chisq.test(x, simulate.p.value=T, B=100000)$p.value >>> for(i in (1:20)){c2x<-c(c2x,chisq.test(x, >> simulate.p.value=T,B=100000)$p.value)}

On Thu, 11 Dec 2003, Jeffrey Chang wrote: > Hello everybody, > > I'm running R 1.8.1 on both Linux and OS X compiled with gcc 3.2.2 and > 3.3, respectively. The following call seems to freeze the interpreter > on both systems: > > chisq.test(matrix(c(233, 580104, 3776, 5786104), 2, 2), > simulate.p.value=TRUE) > > By freeze, I mean, the function call never

>>>>> "Torsten" == Torsten Hothorn <torsten@hothorn.de> >>>>> on Thu, 11 Dec 2003 18:03:07 +0100 (CET) writes: Torsten> On Thu, 11 Dec 2003, Jeffrey Chang wrote: >> Hello everybody, >> >> I'm running R 1.8.1 on both Linux and OS X compiled with >> gcc 3.2.2 and 3.3, respectively. The following

>>>>> "MM" == Martin Maechler <maechler@stat.math.ethz.ch> >>>>> on Thu, 11 Dec 2003 18:29:05 +0100 (CET) writes: >>>>> "Torsten" == Torsten Hothorn <torsten@hothorn.de> >>>>> on Thu, 11 Dec 2003 18:03:07 +0100 (CET) writes: Torsten> On Thu, 11 Dec 2003, Jeffrey Chang wrote:

In running the following example of a loglinear model for the Titanic data, I was surprised to see NaN reported for the Pearson chisq > loglin(Titanic, margin=list(1:3, 4)) 2 iterations: deviation 2.273737e-13 $lrt [1] 671.9622 $pearson [1] NaN $df [1] 15 $margin $margin[[1]] [1] "Class" "Sex" "Age" $margin[[2]] [1] "Survived" Tracing it back,

>>>>> Jan Motl writes: > The chisq.test on line 57 contains following code: > STATISTIC <- sum(sort((x - E)^2/E, decreasing = TRUE)) The preceding 2 lines seem relevant: ## Sorting before summing may look strange, but seems to be ## a sensible way to deal with rounding issues (PR#3486): STATISTIC <- sum(sort((x - E) ^ 2 / E,

Hi, `stats::chisq.test` checks that x and y each have at least 2 levels AFTER filtering on complete cases. It makes sense but the error message is misleading : ?'x' and 'y' must have at least 2 levels? Here?s how to reproduce the issue : x <- structure(c(1L, 1L, 1L, 2L, 1L, 2L), .Label = c("0001", "0003"), class = "factor") y <-

Hello! What kind of calculation perform 'chisq.test', if its argument is a matrix? Thanks for any suggestion! ------------------------------------------------------------ Sincerely yours. Dr. Alessandro Semeria Tel. +39 544 536811 Models and Simulation Lab of Fax. +39 544 538663 The Environment Research Center - Montecatini

I'm using R1.7.0 runing with Win XP. Thanks, ...Tao ???????????????????????????????????????????????????????? >x [,1] [,2] [1,] 149 151 [2,] 1 8 >t(x) [,1] [,2] [1,] 149 1 [2,] 151 8 >chisq.test(x, simulate.p.value=T, B=100000) Pearson's Chi-squared test with simulated p-value (based on 1e+05 replicates) data: x X-squared = 5.2001, df =

Hi I am trying to use this function. Can anyone show me how I would input the following example? Chi-Squared = (40-30)^2 + (20-30)^2 + (30-30)^2 30 30 30 = 3.333 + 3.333 + 0 = 6.666 (p value = 0.036) I want to be able to use different denominators so can you show me how I can do it to accommodate these rather than assuming they are all the

Hi I am running chisq as below and getting a warning. Can anyone tell me the significance or the warning? > chisq.test(c(10 ,4 ,2 ,6 ,5 ,3 ,4 ,4 ,6 ,3 ,2 ,2 ,2 ,4 ,7 ,10 ,0 ,6 ,19 ,3 ,2 ,7 ,2 ,2 ,2 ,1 ,32 ,2 ,3 ,10 ,1 ,3 ,9 ,4 ,10 ,2 ,2 ,4 ,5 ,7 ,6 ,3 ,7 ,4 ,3 ,3 ,7 ,1 ,4 ,2 ,2 ,3 ,3 ,5 ,5 ,4 ), p =c(0.01704142 ,0.017988166 ,0.018224852 ,0.017751479 ,0.017988166 ,0.018224852 ,0.017278107

Hi, I am new to these functions. I'm wondering if there is anyway to save the entire results (all attributes of the result object) from the chisq.test or mantelhaen.test functions? For example, from chisq.test function, you will have statistic, parameter, p.value, expected, etc. in the result list. How can I save all of them in one shot to, says, a text file or csv file? Thank you. - adschai

Hi, I want to analyse a contigency table (3 x 12) with a fisher.test beacause there are cells that are less than 5. ?mmen Anken Baf Belchen H?chi Hof Porti R?m Schmutz Sch?n Sissa Tann class14 7 26 150 2 46 68 126 66 3 31 7 61 class24 7 6 55 5 49 71 93 90 1 18 16 79 class34 1 1 4 3 19 8 29 61

Hi, I looking for a method that use F or Chisq test instead of AIC in a stepwise modelo selection. I try the grasp package using the grasp.step.anova, but It dont work. > library(grasp) Carregando pacotes exigidos: gam Carregando pacotes exigidos: splines Carregando pacotes exigidos: mda Carregando pacotes exigidos: class > data(anorexia,package="MASS") > > m1 <-

Dear all, I would like to do a goodness-of-fit test on my data to see if they follow a mixture of 2 poisson distributions. I have small numbers for observed values. Most of them <5. The chisq.test gives warning message: Chi-squared approximation may be incorrect in: chisq.test(x , p = prob). However, the option sim=TURE would suppress the warning message. Does that mean with the option