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 hypothesis: true probability of success is not equal to 0.24 90 percent confidence interval: 0.1447182 0.3596557 sample estimates: probability of success 0.24 thx much ej
Ethan Johnsons wrote:> 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 hypothesis: true probability of success is not equal to 0.24 > 90 percent confidence interval: > 0.1447182 0.3596557 > sample estimates: > probability of success > 0.24You might consider binconf() in the Hmisc package too: library(Hmisc) binconf(12, 50, method="all") PointEst Lower Upper Exact 0.24 0.130610 0.381691 Wilson 0.24 0.142974 0.374127 Asymptotic 0.24 0.121621 0.358379> thx much > > ej > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Chuck Cleland, Ph.D. NDRI, Inc. 71 West 23rd Street, 8th floor New York, NY 10010 tel: (212) 845-4495 (Tu, Th) tel: (732) 512-0171 (M, W, F) fax: (917) 438-0894
On 19-Oct-06 Ethan Johnsons wrote:> 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?What do you mean by "better"? For a symmetrical 2-sided exact binomial confidence interval, binom.test gives the result quickly and, to within the precision of pbinom, correctly (as I've just verified by hand!). And you can get 1-sided CIs by setting the 'alternative' option, or asymmetrical CI's by finding the two 1-sided CIs (e.g. for conf.level = 0.03 and 0.07) that you want. What do you want to improve on?>> 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 hypothesis: true probability of success is not equal to > 0.24 > 90 percent confidence interval: > 0.1447182 0.3596557r<-12 ; n<-50 1-pbinom(r-1,n, 0.14471815) [1] 0.04999999 1-pbinom(r-1,n, 0.14471816) [1] 0.05000001 pbinom(r,n, 0.35965569) [1] 0.05000001 pbinom(r,n, 0.35965570) [1] 0.05 pbinom(r,n, 0.35965571) [1] 0.04999998> sample estimates: > probability of success > 0.24 > > thx much > > ejBest wishes, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk> Fax-to-email: +44 (0)870 094 0861 Date: 19-Oct-06 Time: 16:53:19 ------------------------------ XFMail ------------------------------
You can also plot an uncertainty distribution of p, using an uninformed prior (uniform(0,1)), using beta(s+1, n-s+1) i.e. x <- seq(0.091, 0.469, length=100) plot(x, dbeta(.x, shape1=13, shape2=39), xlab="x", ylab="Density", main="Uncertainy distribution for p: beta(a = 12+1, b = 50-12+1)", type="l") Cheers, Francisco Dr. Francisco J. Zagmutt College of Veterinary Medicine and Biomedical Sciences Colorado State University>From: Chuck Cleland <ccleland at optonline.net> >To: Ethan Johnsons <ethan.johnsons at gmail.com> >CC: r-help at stat.math.ethz.ch >Subject: Re: [R] binom.test >Date: Thu, 19 Oct 2006 11:27:35 -0400 > >Ethan Johnsons wrote: > > 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 hypothesis: true probability of success is not equal to 0.24 > > 90 percent confidence interval: > > 0.1447182 0.3596557 > > sample estimates: > > probability of success > > 0.24 > >You might consider binconf() in the Hmisc package too: > >library(Hmisc) >binconf(12, 50, method="all") > PointEst Lower Upper >Exact 0.24 0.130610 0.381691 >Wilson 0.24 0.142974 0.374127 >Asymptotic 0.24 0.121621 0.358379 > > > thx much > > > > ej > > > > ______________________________________________ > > R-help at stat.math.ethz.ch mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > >-- >Chuck Cleland, Ph.D. >NDRI, Inc. >71 West 23rd Street, 8th floor >New York, NY 10010 >tel: (212) 845-4495 (Tu, Th) >tel: (732) 512-0171 (M, W, F) >fax: (917) 438-0894 > >______________________________________________ >R-help at stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code._________________________________________________________________ Stay in touch with old friends and meet new ones with Windows Live Spaces
See also the binconf function in the Hmisc package. Ethan Johnsons wrote:> 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 hypothesis: true probability of success is not equal to 0.24 > 90 percent confidence interval: > 0.1447182 0.3596557 > sample estimates: > probability of success > 0.24 > > thx much > > ej >-- Kevin E. Thorpe Biostatistician/Trialist, Knowledge Translation Program Assistant Professor, Department of Public Health Sciences Faculty of Medicine, University of Toronto email: kevin.thorpe at utoronto.ca Tel: 416.946.8081 Fax: 416.946.3297
A quick question, please. 46 e coli lab samples are tested, 6 of them returned positive. So, the best point estimate for p is 6/46 = 0.1304348. For a 95% CI for p, I thought binom.test would give me the correct result, but it seems it is not the right function to use. What is the R function for this?> binom.test(x=6, n=46, p=4/16, conf.level = 0.95)Exact binomial test data: 6 and 46 number of successes = 6, number of trials = 46, p-value = 0.0621 alternative hypothesis: true probability of success is not equal to 0.25 95 percent confidence interval: 0.04940735 0.26256502 sample estimates: probability of success 0.1304348 thx much, ej