Generalized Information Matrix Tests for Detecting Model Misspecification

Richard M. Golden, Steven S. Henley, Halbert White and T. Michael Kashner
Additional contact information
Richard M. Golden: School of Behavioral and Brain Sciences, GR4.1, 800 W. Campbell Rd., University of Texas at Dallas, Richardson, TX 75080, USA
Steven S. Henley: Martingale Research Corporation, 101 E. Park Blvd., Suite 600, Plano, TX 75074, USA
T. Michael Kashner: Department of Medicine, Loma Linda University School of Medicine, Loma Linda, CA 92357, USA

Econometrics, 2016, vol. 4, issue 4, 1-24

Abstract: Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is developed for the purpose of identifying, classifying, and deriving novel model misspecification tests for finite-dimensional smooth probability models. These GIMTs include previously published as well as newly developed information matrix tests. To illustrate the application of the GIMT framework, we derived and assessed the performance of new GIMTs for binary logistic regression. Although all GIMTs exhibited good level and power performance for the larger sample sizes, GIMT statistics with fewer degrees of freedom and derived using log-likelihood third derivatives exhibited improved level and power performance.

Keywords: asymptotic theory; Information Matrix Test; specification analysis; logistic regression; simulation study; information ratio; misspecification (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/2225-1146/4/4/46/pdf (application/pdf)
https://www.mdpi.com/2225-1146/4/4/46/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:4:y:2016:i:4:p:46-:d:82838

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().