Generalized Linear Mixed Models for the Analysis of Categorical Data-Reference-Cited by-同舟云学术

Generalized Linear Mixed Models for the Analysis of Categorical Data

Published:2018 Issue: Volume: Page:
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Container-title:Proceedings of the 2nd International Conference on Medical and Health Informatics - ICMHI '18
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Author:

Li Huayun¹,Jin Laipeng¹,Yu Dongchuan¹

Affiliation:

1. Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Center for Learning Science, Southeast University, Nanjing, China, State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China

Publisher

ACM Press

Reference9 articles.

1. Jaeger, T. F. 2008. Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. J. Mem. Laug. 59, 434--446.

2. Agresti, A. 2002. Categorical data analysis (second ed.). New York, NY: John Wiley & Sons.

3. Winer, B. J., Brown, D. R., & Michels, K. M. 1971. Statistical principles in experimental design. New York: McGraw-Hill

4. Breslow, N. E., and Clayton, D. G. 1993. Approximate inference in generalized linear mixed models. J. Am. Stat. Assoc. 88, 9--25.

5. Li, H., Jia, H., Chung, A., Jin, L., and Yu, D. 2017. The neural correlates of vertical disparity gradient and cue conflict in Panum's limiting case. Brain Cognition. 114, 11--19.

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