Journal
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume 51, Issue 6, Pages 3185-3203Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2019.1710193
Keywords
Conditional maximum likelihood; Gradient test; Psychometrics; Rasch model
Categories
Ask authors/readers for more resources
This study discusses the novel application of the gradient test in the field of psychometrics and compares it with the classical chi square tests. The results confirm that the gradient test has its pros and cons.
In asymptotic theory, the gradient test proposed by Terrell is a recent likelihood-based hypothesis testing approach which can be considered as an alternative to the well-established trinity of likelihood ratio, Rao score, and Wald tests. The gradient test has not yet entered into the mainstream of applied statistics. This is particularly true for the psychometric context. This research discusses a novel application of the gradient test within the conditional maximum likelihood and the Rasch modeling framework. It also investigates some of its finite sample size properties and compares it with the classical trinity of chi square tests by conducting an extensive Monte Carlo study. The results confirm that the gradient test has its pros and cons.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available