The size and power of analytical amd bootstrap corrections to score tests in regression models

Abstract

The paper invsetigation the size and power of analyticaland computer-based (bootstrap) 8nite=saniple adjustments to score tests in a class of regression models. Our results show that score tests can display substantial size distortions and that small-sample adjustments can be quite effective. Bootstrap corrections typically perform slightly better than analytical ones

Keywords:

• Bartlett correction
• Edgeworth expansion
• nonlinear models