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Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences

af Edward E. (Professor and Interim Director of the Agricultural Statistics Laboratory at the University of Arkansas) Gbur, Walter W. (Professor of Statistics at the University of Nebraska Stroup, Kevin S. (Department of Experimental Statistics at Louisiana State University) McCarter, Susan (Statistical consultant at Utah State University) Durham, Linda J. (Professor of Statistics at the University of Florida) Young, Mary (Lead statistical consultant with MCC Statistical Consulting LLC) Christman, Mark (Statistician for the U. S. Department of Agriculture Agricultural Research Service) West, Matthew (Statistician in the mid-Atlantic area (Beltsville Kramer

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Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences af Edward E. (Professor and Interim Director of the Agricultural Statistics Laboratory at the University of Arkansas) Gbur
Bag om Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences

Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences provides readers with an understanding and appreciation for the design and analysis of mixed models for non-normally distributed data. It is the only publication of its kind directed specifically toward the agricultural and natural resources sciences audience. Readers will especially benefit from the numerous worked examples based on actual experimental data and the discussion of pitfalls associated with incorrect analyses.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780891181828
  • Indbinding:
  • Hardback
  • Sideantal:
  • 304
  • Udgivet:
  • 13. marts 2020
  • Størrelse:
  • 235x159x25 mm.
  • Vægt:
  • 658 g.
  • 2-3 uger.
  • 10. december 2024

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Bag om Edward E. (Professor and Interim Director of the Agricultural Statistics Laboratory at the University of Arkansas) Gbur

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Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences provides readers with an understanding and appreciation for the design and analysis of mixed models for non-normally distributed data. It is the only publication of its kind directed specifically toward the agricultural and natural resources sciences audience. Readers will especially benefit from the numerous worked examples based on actual experimental data and the discussion of pitfalls associated with incorrect analyses.

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