Rejecting a null of "inequality" is the standard setup for equivalence testing in medical contexts. Search on "equivalence testing in R" and you will find what you need.
Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Aug 10, 2016 at 3:22 AM, Dominik Marti <d...@inik.ch> wrote: > Hej R helpers > > The standard in statistical hypothesis testing is to reject the null > hypothesis that there is a difference between groups, i.e. to "prove" the > alternative. However, failing to reject the null hypothesis does not prove > it; its rejection just fails. > > Now, as stated in the article "Unicorns do exist: a tutorial on "proving" > the null hypothesis." by David L Streiner (Canadian Journal of Psychiatry, > 48(11) 2003), we can define the null hypothesis to be that there IS a > difference (exceeding a certain value, delta), the alternative hypothesis > being that there is none (or it is at least smaller than delta). If the data > now manages to reject the null hypothesis (of there being a difference > exceeding delta), we can say with a certain probability that there is none. > > Can I do this test in R? And if yes, any leads? > > (In my actual dataset I deal with paired data.) > > Best > Dominik > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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 -- To UNSUBSCRIBE and more, see 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.
