On the robustness of analytical and bootstrtap corrections to score tests in regressios models

Abstract

Two different approaches to obtaining finite-sample corrections to score tests are the analytical and the computational approaches. The former is based either on a Bartletttype correction to the test statistic or on the inversion of an Edgeworth expansion to its null distribution. The latter, on the other hand, is usually based on a bootstrapping resampling scheme. This paper provides a numerical comparison of the size and power properties of these two approaches both under correct model specification and under model misspecification.

Keywords:

• Bootstrap
• Bartlett correction
• Edgeworth expansion
• nonlinear regression
• robustness
• score test