Exact Multivariate Two-Sample Density-Based Empirical Likelihood Ratio Tests Applicable to Retrospective and Group Sequential Studies

TL;DR

This paper introduces an exact, finite-sample, multivariate two-sample test based on density-based empirical likelihood, which is applicable to retrospective and sequential studies, providing high power and accurate Type I Error control.

Contribution

It extends density-based empirical likelihood methods to create an exact multivariate two-sample test applicable in various study designs, with proven asymptotic consistency.

Findings

Demonstrates high and stable power across different scenarios

Provides an exact finite-sample test with controlled Type I Error

Applicable to retrospective and group sequential studies

Abstract

Nonparametric tests for equality of multivariate distributions are frequently desired in research. It is commonly required that test-procedures based on relatively small samples of vectors accurately control the corresponding Type I Error (TIE) rates. Often, in the multivariate testing, extensions of null-distribution-free univariate methods, e.g., Kolmogorov-Smirnov and Cramer-von Mises type schemes, are not exact, since their null distributions depend on underlying data distributions. The present paper extends the density-based empirical likelihood technique in order to nonparametrically approximate the most powerful test for the multivariate two-sample (MTS) problem, yielding an exact finite-sample test statistic. We rigorously establish and apply one-to-one-mapping between the equality of vectors distributions and the equality of distributions of relevant univariate linear projections. In this framework, we prove an algorithm that simplifies the use of projection pursuit, employing only a few of the infinitely many linear combinations of observed vectors components. The displayed distribution-free strategy is employed in retrospective and group sequential manners. The asymptotic consistency of the proposed technique is shown. Monte Carlo studies demonstrate that the proposed procedures exhibit extremely high and stable power characteristics across a variety of settings. Supplementary materials for this article are available online.