Abstract
We propose a simplified version of the partially observed quasi-information matrix (Poquim) method for inference about non-Gaussian linear mixed models and show its computational advantage over the original method. We illustrate the difference, and compare performance of the simplified version with Poquim as well as the normality-based method in simulation studies. An example of real-data analysis is considered.
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Acknowledgements
The research of Thuan Nguyen and Jiming Jiang are partially supported by the National Science Foundation of the United States Grants DMS-1914760 and DMS-1914465, respectively. Jiming Jiang’s research is also supported by the National Science Foundation Grant DMS-1713120. The authors are grateful to the reviewers’ comments that have helped improve the work and presentation.
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Nguyen, T., Jiang, J. Simplified partially observed quasi-information matrix. Comput Stat 38, 171–189 (2023). https://doi.org/10.1007/s00180-022-01221-8
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DOI: https://doi.org/10.1007/s00180-022-01221-8