The adverse effect of small sample sizes, excessive nonresponse rate, and high dimensionality on likelihood ratio test statistic
can be reduced by integrating with respect to a prior distribution. If information regarding the prior is too general (for
example, only a parametric family can be specified), this distribution can be chosen from a principle of the most powerful
testing. We propose the ... [Show full abstract] integrated most powerful test in the presence of missing data. This test can be used as a viable alternative
to the maximum likelihood.
KeywordsParametric hypothesis testing–Most powerful test–Likelihood ratio–Missing data–Maximum likelihood