Equivalence testing of mean vector and covariance matrix for multi-populations under a two-step monotone incomplete sample

This paper investigates the hypothesis testing of a mean vector and covariance matrix for multi-populations in the context of two-step monotone incomplete data drawn from Np+q(μ,Σ), a multivariate normal population with mean μ and covariance matrix Σ. Three null hypotheses are considered, and the likelihood ratio criterion and Wald-type criterion are derived. On the basis of numerical simulations, the test that employs the Wald-type criterion is recommended.