The other one I should have mentioned: 5.1: Use the glm function with family = poisson. The counts are the y variable and the x variable is either 0/1 or a 2 level factor indicating which group the values come from. The p-value for the slope of x tests for a difference in the 2 groups.
5.2 if this is just to make someone happy who always wants a p-value, but doesn't understand it and will never actually use it, then use runif. 5.3 ... -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Greg Snow > Sent: Thursday, December 20, 2007 1:20 PM > To: Mark Gosink; r-help@r-project.org > Subject: Re: [R] comparing poisson distributions > > There are a few different options that you can try depending > on your problem and your preferences: > > 1. For large lambda the poisson can be approximated by a > normal, for large n (even for small lambda) the mean is > approximately normal due to the central limit theorem. So if > your lambda and n are large enough in combination then you > could just do a standard 2 sample t-test (t.test > function) and use the approximate p-value from there. > > 2. Fit 2 models by maximum likelihood, one in which both > lambdas are equal and one in which they can differ (fitdistr > from MASS may help, or look at optim and friends), then do a > likelihood ratio test on the differences (-2 * likelihood > diff is approx chisquared(1) under the null). > > 3. Do a permutation test: find the difference in the > means/medians/(other stat of interest) between the 2 samples, > then permute the samples randomly (create 2 samples of the > same sizes from the original data values, but with random > assignment as to which group a value goes into) and find the > same difference, repeate a bunch of times (like 1998) and > combine all the differences found into a vector, plot the > histogram of the values and look at where the original > difference fits into the distribution. The number of values > that are as or more extreeme than the original value is your p-value. > > 4. Create logical bins for values (e.g. 0-1, 2-3, 4-6, 7+) > and count how many from each group fall in each bin, use > prop.test or chisq.test to see if the proportions differ. > > 5. Probably some others that don't come to mind right now. > > Hope this helps, > > -- > Gregory (Greg) L. Snow Ph.D. > Statistical Data Center > Intermountain Healthcare > [EMAIL PROTECTED] > (801) 408-8111 > > > > > -----Original Message----- > > From: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] On Behalf Of Mark Gosink > > Sent: Tuesday, December 18, 2007 12:31 PM > > To: r-help@r-project.org > > Subject: [R] comparing poisson distributions > > > > Hello all, > > > > I would like to compare two sets of count data > which form > > Poisson distributions. I'd like to generate some sort of p-value of > > the likely-hood that the distributions are the same. Thanks > in advance > > for your advice. > > > > > > > > Cheers, > > > > Mark > > > > > > > > Mark Gosink, Ph.D. > > > > Head of Computational Biology > > Scripps Florida > > 5353 Parkside Drive - RFA > > Jupiter, FL 33458 > > tel: 561-799-8921 > > fax: 561-799-8952 > > [EMAIL PROTECTED] > > > > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org 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. > > > > ______________________________________________ > R-help@r-project.org 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. > ______________________________________________ R-help@r-project.org 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.
