Proving (instead of rejecting) that two groups are actually equal
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 <dom at 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
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