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Generalized, Linear, and Mixed Models
Abstract
An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m
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Citations
Cited by
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Bolger, N., Davis, A., & Rafaeli, E. (2003) · Annual Review of Psychology · doi:10.1146/annurev.psych.54.101601.145030 · Cited by 3,843
Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists.
Nakagawa, S., & Schielzeth, H. (2010) · Biological Reviews · doi:10.1111/j.1469-185x.2010.00141.x · Cited by 2,584
Guskiewicz, K. M., McCrea, M., Marshall, S. W., Cantu, R. C., Randolph, C., Barr, W., Onate, J. A., & Kelly, J. P. (2003) · JAMA · doi:10.1001/jama.290.19.2549 · Cited by 1,712
Leventhal, A. M., Strong, D. R., Kirkpatrick, M. G., Unger, J. B., Sussman, S., Riggs, N. R., Stone, M. D., Khoddam, R., Samet, J. M., & Audrain-McGovern, J. (2015) · JAMA · doi:10.1001/jama.2015.8950 · Cited by 913
Metadata
- Authors
- McCulloch, C. E., & Searle, S. R.
- Venue
- Wiley Series in Probability and Statistics
- Publisher
- Wiley
- Published
- 2000-12-18
- ISSN
- 1940-6347 (ISSN-L)
- OpenAlex
- W1565240145
- Cited by
- 2,994
- References
- 0
- FWCI
- 14.99
- Type
- book
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Generalized, Linear, and Mixed Models. https://app.cochat.ai/papers/10.1002/0471722073
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- McCulloch, C. E., & Searle, S. R. (2000). Generalized, Linear, and Mixed Models. Wiley Series in Probability and Statistics. https://doi.org/10.1002/0471722073
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
