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Beginner's question about ptrend. What package to use in R and a general explanation of the statistics.
3 messages · Bob Briggs, Sarah Goslee, David Winsemius
Hi,
On Sun, Oct 16, 2011 at 6:24 PM, Bob Briggs <rbriggs1 at hotmail.com> wrote:
Hello I'm wanting to understand more about ptrend (a statistical explanation via an internet website if possible) and also to know what package in R would produce a ptrend. Appreciate any help I can get on this as I'm trying to read and understand an epidemiological paper and data and reproduce similar results for my own understanding.
Given that I'm not an epidemiologist, and have no idea what a ptrend is, and that you didn't actually explain what kind of beast it might be: If you go to http://www.rseek.org and search for ptrend, you will get several R packages that use that term, a few posts from the R-help list, and a pile of websites that might be helpful. Sarah
Thanks Meredith
Sarah Goslee http://www.functionaldiversity.org
On Oct 17, 2011, at 8:04 AM, Sarah Goslee wrote:
Hi, On Sun, Oct 16, 2011 at 6:24 PM, Bob Briggs <rbriggs1 at hotmail.com> wrote:
Hello I'm wanting to understand more about ptrend (a statistical explanation via an internet website if possible) and also to know what package in R would produce a ptrend. Appreciate any help I can get on this as I'm trying to read and understand an epidemiological paper and data and reproduce similar results for my own understanding.
Given that I'm not an epidemiologist, and have no idea what a ptrend is, and that you didn't actually explain what kind of beast it might be:
It seems likely that it is a test for linear trend in odds ratios or rate ratios in an ordered set of proportions. It was taught us (epidemiologists) in the courses before we got our hands on logistic regression. In my training it was called the Cochran-Armitage test for trend: http://en.wikipedia.org/wiki/Cochran-Armitage_test_for_trend You get such test when you use prop.trend.test {stats}. It is basically a linear regression (or a Pearson correlation) with a "chi-square test" using the weighted departures of counts in cells from an expected value set by the overall proportion. (Look at the code for prop.trend.test. It makes perfect sense that a set of squared departures from an expected value set by the mean could be cast as a "chi-square test".) I do not know of any advantages for the test over logistic regression or Poisson regression. You can take an ordered factor (or a non-ordered on if the levels are properly set up, coerce to numeric and do logistic regression with the numeric result and get pretty much the same result, and you would be doing so in the context of a much more flexible modeling environment. So I see it mainly as of historical interest, something to use when you only have a device that cannot run R.
David. > > If you go to http://www.rseek.org and search for ptrend, you will get > several R packages that use that term, a few posts from the R-help > list, and a pile of websites that might be helpful. > > > Sarah > > >> Thanks >> Meredith David Winsemius, MD West Hartford, CT