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Analysis of Variance, Design, and Regression
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Analysis of Variance, Design, and Regression : Linear Modeling for Unbalanced Data, Second Edition

Book Details

Format Paperback / Softback
ISBN-10 036773740X
ISBN-13 9780367737405
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 18th, 2020
Print length 636 Pages
Weight 1,152 grams
Dimensions 17.70 x 25.30 x 4.10 cms
Ksh 10,300.00
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This second edition focuses on modeling unbalanced data. It presents many new topics, including new chapters on logistic regression, log-linear models, and time-to-event data. It shows how to model main-effects and interactions and introduces nonparametric, lasso, and generalized additive regression models. The text carefully analyzes small unba

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.



New to the Second Edition





  • Reorganized to focus on unbalanced data


  • Reworked balanced analyses using methods for unbalanced data


  • Introductions to nonparametric and lasso regression


  • Introductions to general additive and generalized additive models


  • Examination of homologous factors


  • Unbalanced split plot analyses


  • Extensions to generalized linear models


  • R, Minitab®, and SAS code on the author’s website




The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.


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