Good morning,
My subject is mostly a request about a statistical test and not about the use of JMP, although I will have a small question about this at the end of the discussion.
I am completely confused about the use of two different methods of the TOST / Schuirmann average equivalence test (I am talking about equivalence and not average comparison!).
Here is the data:
Average 1: 101.0
Average 2: 101.9
Lower accepted bias (B-): -1
Upper bias accepted (B+): +2
σ1: 0.9
σ2: 1.5
n1:6
n2: 6
α: 0.05
tcritical: 1.81
Varpool: 1.52
σpool: 1.23
Here are the two methods used to assess equivalence.
1st method:
Calculation of the confidence interval:
CI = (X1 - X2) +/- t(1-2α,n1 + n2 -2)*σpool*(1/n1 + 1/n2)
Which gives [ 0.17 - 1.66 ], the interval being included between the limits of acceptance of the equivalence [ -1 and 2 ], the test concludes with the equivalence of the two averages.
2nd method:
Calculation of TLower and TUpper statistics.
TL = [(X1 - X2) - B-] / σpool * Root (1/n1 + 1/n2).
TU = [(X1 - X2) - B+] / σpool * Root (1/n1 + 1/n2).
I find for TLower: 2.69 and TUpper: -1.52.
T critical with α: 0.05 and dof 10: 1.81.
With the two t values, I cannot find the equivalence (t value -1.52 > -1.81).
So I would like to understand why this difference? Knowing that the confidence interval approach remains extremely rare (see link: https://www.ncbi.nlm.nih.gov/pmc/art...MMC-25-123.pdf )
Otherwise for the use of JMP (version 17.0 in my case), when I launch an equivalence test, JMP asks for a difference value to certify from when the non-equivalence is considered, but I cannot have a off-center bias (my example: -1; +2), since only one value must be entered.
Thank you in advance for your feedback on this subject ^^!
Cordially !
