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Home > Reference > Research and information: general > Data science and analysis: general > Designing Experiments and Analyzing Data: A Model Comparison Perspective, Second Edition
Designing Experiments and Analyzing Data: A Model Comparison Perspective, Second Edition

Designing Experiments and Analyzing Data: A Model Comparison Perspective, Second Edition


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About the Book

Designed to serve as either a graduate-level text or reference book for experimental design, this book should be of use in psychology, education and statistics departments. The book promotes a model comparison perspective rather than the more traditional variance partitioning approach. This approach offers several advantages. Firstly, it better prepares students to understand the logic behind choosing the best technique for a particular design. Secondly, focusing on definitional versus computational formulae allows for a heavier reliance on statistical packages to perform the actual computations, freeing the reader to spend more time on the conceptual understanding versus the number crunching. Finally, the model comparison approach allows for the introduction of more complex topics, generally omitted from other books.

Table of Contents:
Contents: Preface. Part I: Conceptual Bases of Experimental Design and Analysis. The Logic of Experimental Design. Introduction to the Fisher Tradition. Part II: Model Comparisons for Between-Subjects Designs. Introduction to Model Comparisons: One-Way Between-Subjects Designs. Individual Comparisons of Means. Testing Several Contrasts: The Multiple-Comparison Problem. Trend Analysis. Two-Way Between-Subjects Factorial Designs. Higher Order Between-Subjects Factorial Designs. Designs With Covariates: ANCOVA and Blocking. Designs With Random or Nested Factors. Part III: Model Comparisons for Designs Involving Within-Subjects Factors. One-Way Within-Subjects Designs: Univariate Approach. Higher-Order Designs With Within-Subjects Factors: Univariate Approach. One-Way Within-Subjects Designs: Multivariate Approach. Higher Order Designs With Within-Subjects Factors: Multivariate Approach. Part IV: Alternative Analysis Strategies. An Introduction to Multilevel Models for Within-Subjects Designs. An Introduction to Multilevel Hierarchical Mixed Models: Nested Designs. Appendices: Statistical Tables. Part 1. Linear Models: The Relation Between ANOVA and Regression. Part 2. A Brief Primer of Principles of Formulating and Comparing Models. Notes. Solutions to Selected Exercises. References.

Review :
"Overall, this is an excellent resource for those designing and analyzing experiments, and for those wishing to consolidate their knowledge of individual designs into a unified conceptual framework." —American Statistician


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Product Details
  • ISBN-13: 9780805837186
  • Publisher: Taylor & Francis Inc
  • Publisher Imprint: Routledge Academic
  • Edition: New edition
  • Language: English
  • No of Pages: 1104
  • Sub Title: A Model Comparison Perspective, Second Edition
  • Width: 152 mm
  • ISBN-10: 0805837183
  • Publisher Date: 01 Jul 2003
  • Binding: Hardback
  • Height: 229 mm
  • No of Pages: 1104
  • Returnable: N
  • Weight: 2177 gr


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