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I also wanted to dig into this. The null hypothesis and burden-of-proofs change between p tests and equivalence testing, right? P tests: null hypothesis is tha
by cjslep 8y ago
I also wanted to dig into this. The null hypothesis and burden-of-proofs change between p tests and equivalence testing, right?
P tests: null hypothesis is that there is nothing different, burden of proof to suggest there is a difference.
Equivalence testing: null hypothesis is that there is something different, burden of proof to suggest there is no difference.
But maybe this is just a misapplied p-test? So while the "RESULTS" section of the paper is fine:
No differences between trials ( P > 0.05) were found in the overall plasma triglyceride, glucose, or insulin responses during the HFGTT.
The "CONCLUSION" section is where they invert the statistics of their own study and literally suggest a p-test-able difference despite their results section literally concluding a p-test-able non-difference:
These data indicate that physical inactivity (e.g., sitting ~13.5 hrs/day and <4,000 steps/day) creates a condition whereby people become "resistant" to the metabolic improvements that are typically derived from an acute bout of aerobic exercise (i.e., exercise resistance).
- Darmani 8y agoYes, they used a test designed to find a difference between two groups, and it failed to report a difference. Your analysis of that is correct, although the terminology "p-test" to describe "a statistical test designed to find a difference" is not. I don't know the general term for this class of tests. The definition of p-values is a bit wonky (there's actually a set of null hypotheses rather than a single one, and it involves a supremum over that set), but the line "if we're wrong, then the chance of seeing this data is at most p" is pretty accurate. All kinds of frequentist statistical tests use them, including equivalence tests.