search for: truax

...packages. I am really pleased to have access to them through R which, I have to say, is an amazing piece of software. I am only sorry that I haven't found it until now. But, to my question. Does anyone know if there is a package developed for evaluating clinical significance using Jacobson and Truax's, or variations thereof, procedures? Cheers Alistair Campbell School of Psychology James Cook University Townsville QLD [[alternative HTML version deleted]]

...packages. I am really pleased to have access to them through R which, I have to say, is an amazing piece of software. I am only sorry that I haven't found it until now. But, to my question. Does anyone know if there is a package developed for evaluating clinical significance using Jacobson and Truax's, or variations thereof, procedures? Cheers Alistair Campbell School of Psychology James Cook University Townsville QLD

...suggested on this very list a few weeks ago. This function will plot nested breakdowns of numeric values by one or more factors. It seems quite useful for visualizing the deviations in successively finer divisions of the data. Comments are welcome. clinsig (1.0-1 - basically the Jacobsen & Truax clinical significance tests with a few extras) has had a few rough edges knocked off with continued use. I would also like to hear from users of this little package. Have fun. Jim

After many long hours and a lot of help from Tom I was able to get IPSEC running on kernel 2.6, here''s a step-by-step for Getting Policy match working.. Hope it helps Adding Policy Match Support to Kernel 2.6 JJ Truax jtruax at optivel dot com This is a step by step how-to for adding policy match support to a 2.6 kernel. For information on configuring IPSEC for the Kernel 2.6 see Tom Eastep''s How-to IPSEC using Linux Kernel 2.6 http://www.shorewall.net/IPSEC-2.6.html Distro Info: I''m using De...

Dear mailing list, For two normal distributions, e.g: r1 =rnorm(20,5.2,2.1) r2 =rnorm(20,4.2,1.1) plot(density(r2), col="blue") lines(density(r1), col="red") Is there a way in R to compute/estimate the point(s) x where the density of the two distributions cross (ie where x has equal probability of belonging to either of the two distributions)? Many Thanks Eleni