search for: clinicalresearch

Hi, I'm wondering if anyone can point me to a function that will allow me to do a ranking that treats ties differently than rank() provides for? I'd like a method that will assign to the elements of each tie group the largest rank. An example: For the vector 'v', I'd like the method to return 'rv' v: 1 2 3 3 3 4 5 5 6 7 rv: 1 2 5 5 5 6 8 8 9 10 Thanks,

Hi, I would like to do a MannWitney test. Can anyone help me with the propper command? Thanks, Margarida

Hello, I've tried to analyze some data with a CMH test. My 3 dimensional contingency tables are 2x2xN where N is usually between 10 and 100. The problem is that there may be 2 strata with opposite counts (the 2x2 contigency table for these are reversed), producing opposite odds ratios that cancle out in the overall statistics. These opposite counts are very important for my analysis, since

...---------------------------- Knut M. Wittkowski, PhD,DSc ------------------------------------------ The Rockefeller University, GCRC Experimental Design and Biostatistics 1230 York Ave #121B, Box 322, NY,NY 10021 +1(212)327-7175, +1(212)327-8450 (Fax) kmw at rockefeller.edu http://www.rucares.org/clinicalresearch/dept/biometry/

Hi, I use ks.test or lillie.test to verify a normal distribution. It's performed for a group My users use SigmaStat software and a One Way ANOVA on several groups In the result page there is a probability value to determine if Normality test is failed or passed So, how can i retrieve this probability value on several groups? Is there another function in R to verify normality on several

Hello, I am analysing several samples whose sizes are from 9 to 110. I would like to test their distribution with R, whether they are normal or not. I wonder which test for normality from R should I use . Thank you for help. Samuel Samuel BERTRAND Doctorant Laboratoire de Biomecanique LBM - ENSAM - CNRS UMR 8005 151, bd de l'Hopital 75013 PARIS Tel. +33 (0) 1 44 24 64 53 Fax +33 (0) 1

Hi. I'm going to introduce the R-package for a group of medical doctors later this week and is a little confused about there use of a test named "willcoxon-pratt" for testing if the clinical and biochemical markers has decreased significantly after the use of some drugs for a group of patients. Looking into the R-functions I would in R recommand using a matched-pairs Wilcoxon

I am trying to `cut' a continuous variable into contiguous classes containing approximately an equal number of observations. I thought quantile() was the appropriate function to use in order to find the breakpoints, but I end up with classes of different sizes - see example below. Does anybody have an explanation for that? And what is the `recommended' way of computing what I am looking