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In this paper, we develop modified versions of the likelihood ratio test formultivariate heteroskedastic errors-in-variables regression models. The errorterms are allowed to follow a multivariate distribution in the elliptical classof distributions, which has the normal distribution as a special case. Wederive the Skovgaard adjusted likelihood ratio statistics, which follow achi-squared distribution with a high degree of accuracy. We conduct asimulation study and show that the proposed tests display superior finitesample behavior as compared to the standard likelihood ratio test. Weillustrate the usefulness of our results in applied settings using a data setfrom the WHO MONICA Projection cardiovascular disease.

Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error