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Gradient test for generalised linear models with random effects

da Silva-Junior, A.H.M.; Einbeck, J.; Craig, P.S.

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Authors

A.H.M. da Silva-Junior



Contributors

J. F. Dupuy
Editor

J. Josse
Editor

Abstract

This work develops the gradient test for parameter selection in generalised linear models with random effects. Asymptotically, the test statistic has a chi-squared distribution and the statistic has a compelling feature: it does not require computation of the Fisher information matrix. Performance of the test is verified through Monte Carlo simulations of size and power, and also compared to the likelihood ratio, Wald and Rao tests. The gradient test provides the best results overall when compared to the traditional tests, especially for smaller sample sizes.

Citation

da Silva-Junior, A., Einbeck, J., & Craig, P. (2016). Gradient test for generalised linear models with random effects. In J. F. Dupuy, & J. Josse (Eds.), Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France (213-218)

Conference Name International Workshop on Statistical Modelling
Conference Location Rennes, France
Start Date Jul 4, 2016
End Date Jul 8, 2016
Acceptance Date Mar 25, 2016
Publication Date Jul 8, 2016
Deposit Date Jul 25, 2016
Publicly Available Date Mar 28, 2024
Volume 1
Pages 213-218
Book Title Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France.
Public URL https://durham-repository.worktribe.com/output/1150457
Publisher URL http://www.statmod.org/workshops_archive_proceedings_2016.htm
Additional Information Conference date: 4-8 July 2016

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