Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Antonio Hermes M. da Silva-Júnior, Damião Nóbrega da Silva, Silvia L. P. Ferrari
Title: mdscore: An R Package to Compute Improved Score Tests in Generalized Linear Models
Abstract: Improved score tests are modifications of the score test such that the null distribution of the modified test statistic is better approximated by the chi-squared distribution. The literature includes theoretical and empirical evidence favoring the improved test over its unmodified version. However, the developed methodology seems to have been overlooked by data analysts in practice, possibly because of the difficulties associated with the computation of the modified test. In this article, we describe the mdscore package to compute improved score tests in generalized linear models, given a fitted model by the glm() function in R. The package is suitable for applied statistics and simulation experiments. Examples based on real and simulated data are discussed.

Page views:: 3164. Submitted: 2011-12-16. Published: 2014-10-24.
Paper: mdscore: An R Package to Compute Improved Score Tests in Generalized Linear Models     Download PDF (Downloads: 5830)
mdscore_0.1-2.tar.gz: R source package Download (Downloads: 360; 7KB)
v61c02.R: R example code from the paper Download (Downloads: 420; 16KB)

DOI: 10.18637/jss.v061.c02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.