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Mixed Models for Data Analysts

Mixed Models for Data Analysts


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About the Book

Mixed model methods are useful in a variety of applications, including medicine, biostatistics, and agriculture. "Mixed Models for Data Analysts" balances theory and practice to illustrate and demonstrate mixed model methodology. The authors, all highly regarded researchers in the field, demonstrate the strength of the mixed model approach through numerous examples using S-PLUS and other computer packages. Integration of theory with "how to do it," interesting, real data sets from wide-ranging applications, and computer code available on the Internet make this a valuable guide for researchers and practitioners interested in using linear mixed models.

Table of Contents:
An Overview of Linear Models. Linear Mixed Models. Multistratum Analysis of Variance. Random Coefficients. Nonlinear Models. Spatial Analysis of a Field Experiment. Mutivariate Spatial Analysis. Analysis of a Series of Field Experiments. LongitudinalData Analysis. Extensions to Non-Normal Data. Markov Chain Monte Carlo Methods.


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Product Details
  • ISBN-13: 9781584882602
  • Publisher: Taylor & Francis Inc
  • Publisher Imprint: CRC Press Inc
  • Language: English
  • ISBN-10: 1584882603
  • Publisher Date: 15 Feb 2009
  • Binding: Hardback
  • Returnable: N


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