similar to: Make sign test show test statistics

Dear all, I'm quite sure that this is a stupid question, but I'll ask anyway. I want to perform an ANCOVA with two continuous factors and three categorical factors. Plant population growth rate (GR) = dependent variable Seed reduction due to herbivory (SR) = continuous explanatory variable Herbivore species (HS, 2 levels) = categorical explanatory variable Population (Pop, 24 levels) =

I believe the binom.test procedure is producing one tailed p values rather than the two tailed value implied by the alternative hypothesis language. A textbook and SAS both show 2*9.94e-07 = 1.988e-06 as the two tailed value. As does the R summation syntax from R below. It looks to me like the alternative hypothesis language should be revised to something like " ... greater than or equal

I need to run binomial tests (binom.test) on a large set of data, stored in a table - 600 tests in total. The values of x are stored in a column, as are the values of n. The data for each test are on a separate row. For example: X N 11 19 9 26 13 21 13 27 18 30 It is a two-tailed test, and P in all cases is 0.5. My question is: Is there a quicker way of running these tests without having to

hello, i did several binomial tests and noticed for one sparse dataset that binom.test(1,1,0.5) gives a p-value of 1 for the null, what i can't quite grasp. that would say that the a prob of 1/2 has p-value of 0 ?? - i must be wrong but can't figure out the right interpretation.. best, kay ----- ------------------------ Kay Cichini Postgraduate student Institute of Botany Univ. of

Hi David, Thanks for your comments! I just want to add that I think it would neat if the entry values could map into multi-location dbg.values and DBG_VALUEs that are being proposed on this list. For example, if we have: int local = param1 + param2 + 123; I think it would be good if we would be able to to represent the four different permutations of the values of the parameters being

Hello everybody. Does anyone else find the last test in the following sequence odd? Can anyone else reproduce it or is it just me? > binom.test(100,200,0.13)$p.value [1] 2.357325e-36 > binom.test(100,200,0.013)$p.value [1] 6.146546e-131 > binom.test(100,200,0.0013)$p.value [1] 1.973702e-230 > binom.test(100,200,0.00013)$p.value [1] 0.9743334 (R 1.5.1, Linux RedHat 7.1) --

Full_Name: Robert W. Baer, Ph.D. Version: 1.6.2 OS: Windows 2000 Submission from: (NULL) (198.209.172.106) Problem: prop.test() does not seem to produce appropriate confidence intervals for the case where the vector length of x and n is one. (I am not certain about higher vector lengths.) As an example, I include x=6 and n=42 which has a mean proportion of 0.115. When I calculate the 95% CI

The only references to this I can find searching the archives are to a student who asked in relation to his course work on a stats course. Promise I'm not doing that! I have a situation in which we want to test proportions against an expected proportion, binom.test() is great. I'd like to do some post hoc power tests (the x and n were beyond our control in the survey as all we could set

Hello, curl-7.16.0 breaks compilation of vorbis-tools-1.1.1 - please see http://curl.haxx.se/mail/archive-2006-11/0046.html for details. According to Daniel Stenberg, CURLOPT_MUTE is deprecated. Could you please update vorbis-tools code so it won't use deprecated features of 'curl' ? Should I file a bug report regarding this issue ? Thanks, Sergei. Applications From Scratch:

On Wed, Feb 22, 2023 at 04:52:35PM +0100, Laszlo Ersek wrote: ... > Seems sane to me in general, except for the fact that the documentation > at <https://curl.se/libcurl/c/CURLSHOPT_SHARE.html> writes: > > """ > CURL_LOCK_DATA_CONNECT > > Put the connection cache in the share object and make all easy handles > using this share object share the

I am trying to find a definition for the two-tailed exact binomial test but have been unsuccessful. Can you help? --------------------------------- [[alternative HTML version deleted]]

Hi, I want to compute p value of sign test for sample size=15 from normal distr., sd=0.5, mean=1, alternative should be two sided. Is this code correct in this situation? binom.test(sum(rnorm(15,1,0.5)>0),15,p=0.5,alternative="two")$p.value Or should I use another code (function) e.g. rbinom? Thank you very much. kind regards, T. Bal [[alternative HTML version deleted]]

Hi all, I am wondering whether there is a small bug in the binom.test function of the ctest library (I'm using R 1.6.0 on windows 2000, but Splus 2000 seems to have the same behaviour). Or perhaps I've misunderstood something. the command binom.test(11,100,p=0.1) and binom.test(9,100,p=0.1) give different p-values (see below). As 9 and 11 are equidistant from 10, the mean of the

Full_Name: Petr Savicky Version: 2.4.0 OS: Fedora Core release 2 Submission from: (NULL) (62.24.91.47) the error is > binom.test(0.56*10000,10000) Error in binom.test(0.56 * 10000, 10000) : 'x' must be nonnegative and integer while > binom.test(5600,10000) yields correct result. The same error occurrs for > binom.test(0.57*10000,10000)

Dear R Users, Is the p-value reported in a two-tailed binomial exact test in error or is it a feature? If it is a feature, could someone provide a reference for its two-tailed p-value computations? Using Blaker's (2000 - Canad. J. Statist 28: 783-798) approach,the p-value is the minimum of the two-tailed probabilities $P \left(Y\geq y_{obs}\right)$ and $P\left(Y\leq y_{obs}\right)$

Hello all, I am trying to understand the different results I am getting from the following 3 commands: chisq.test(c(62,50), p = c(0.512,1-0.512), correct = F) # p-value = 0.3788 binom.test(x=62,n=112, p= 0.512) # p-value = 0.3961 2*(1-pbinom(62,112, .512)) # p-value = 0.329 Well, the binom.test was supposed to be "exact" and give the same results as the pbinom, while the chisq.test

R-experts: A quick question, please. >From a lab exp, I got 12 positives out of 50. To get 90% CI for this , I think binom.test might be the one to be used. Is there a better way or function to calculate this? > binom.test(x=12, n=50, p=12/50, conf.level = 0.90) Exact binomial test data: 12 and 50 number of successes = 12, number of trials = 50, p-value = 1 alternative

Hi, I noticed this problem on my home desktop running FC4 and again on my laptop running FC5. Both have previously compiled and passed make check-all on 2.3.1 svn revisions from 10 days ago or so. On both these machines, make check-all is consistently failing (4 out of 4 attempts on the FC 4 desktop and 3 out of 3 on the FC 5 laptop) in the p-r-random-tests tests. This is with both default

R. 1.1.0 The example below is self explanatory. ## 1 ## # works fine > binom.test((50*.64),50,.5,alt='g') ... Exact binomial test ... ## 2 ## # WHAT ! ? > binom.test((50*.65),50,.5,alt='g') Error in binom.test((50 * 0.65), 50, 0.5, alt = "g") : x must be an

Hi Folks, The recent correspondence about "strange fisher.test result", and especially Peter Dalgaard's reply on Tue 03 April 2007 (which I want to investigate further) led me to take a close look at the code for binom.test(). I now have a query! The code for the two-sided case computes the p-value as follows: if (p == 0) (x == 0) else if (p == 1) (x == n)