ABSTRACT
Parameters: k = number of univariate variables being considered simultaneously µ = mean vector (k × 1) Σ = covariance matrix (k × k) µ0 = target mean vector (k × 1) Δ = tolerable distance between μ and μ0, that is, noninferiority is defined as:
µ − µ ≤ ∆0
where:
d d dk1 2
2 2 2δ = + + +
where:
d d
dk
2δ =
is a k × 1 column vector. 1 – β = power to reject the null if
0µ − µ > ∆.
