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Variance component testing in generalised linear models with random effects
Abstract
There is considerable interest in testing for overdispersion, correlation and heterogeneity across groups in biomedical studies. In this paper, we cast the problem in the framework of generalised linear models with random effects. We propose a global score test for the null hypothesis that all the variance components are zero. This test is a locally asymptotically most stringent test and is robust in the special sense that the test does not require specifying the joint distribution of the random effects. We also propose individual score tests and their approximations for testing the variance components separately. Both tests can be easily implemented using existing statistical software. We illustrate these tests with an application to the study of heterogeneity of mating success across males and females in an experiment on salamander matings, and evaluate their performance through simulation.
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Cited by
Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,356
Self-citationPowerful SNP-Set Analysis for Case-Control Genome-wide Association Studies
Wu, M. C., Kraft, P., Epstein, M. P., Taylor, D. M., Chanock, S. J., Hunter, D. J., & Lin, X. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.05.002 · Cited by 592
Self-citationZhao, N., Chen, J., Carroll, I. M., Ringel-Kulka, T., Epstein, M. P., Zhou, H., Zhou, J. J., Ringel, Y., Li, H., & Wu, M. C. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.04.003 · Cited by 306
Liu, L., Sabo, A., Neale, B. M., Nagaswamy, U., Stevens, C., Lim, E., Bodea, C. A., Muzny, D., Reid, J. G., Banks, E., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003443 · Cited by 135
Joint analysis of SNP and gene expression data in genetic association studies of complex diseases
Huang, Y.-T., VanderWeele, T. J., & Lin, X. (2014) · The Annals of Applied Statistics · doi:10.1214/13-aoas690 · Cited by 88
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Metadata
- Authors
- Lin, X.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1997-06-01
- Volume
- 84
- Issue
- 2
- Pages
- 309-326
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2035196541
- Cited by
- 354
- References
- 0
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lin, X. (1997). Variance component testing in generalised linear models with random effects. Biometrika. https://doi.org/10.1093/biomet/84.2.309
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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