About the Book: Overview
Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis.
The authors (Scott E. Maxwell, Harold D. Delaney, and Ken Kelley) first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books.
Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter’s content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available on this website (DesigningExperiments.com), and extensive sets of exercises help develop a deeper understanding of the subject.
Detailed solutions for some of the exercises and realistic data sets are also provided on this website. The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. We aim for the book to be useful for students and researchers seeking the optimal way to design their studies and analyze the resulting data.
The book’s web page at Routledge is here. Instructors considering the book for adoption can request an examination copy here.
Citation
Maxwell, S. E., Delaney, H. D., & Kelley, K. (2018).
Designing experiments and analyzing data: A model comparison perspective (3rd ed).
New York, NY: Routledge.
About the Authors
Scott E. Maxwell
Scott E. Maxwell is the Fitzsimons Professor of Psychology at the University of Notre Dame. His research interests are in the areas of research methodology and applied behavioral statistics, with much of his recent work focusing on statistical power and accuracy in parameter estimation, especially in randomized designs.
He has served as editor of Psychological Methods; received the Samuel J. Messick Award for Distinguished Scientific Contributions by the American Psychological Association’s Division of Evaluation, Measurement, and Statistics; and has received multiple teaching awards.
Harold D. Delaney
Harold D. Delaney is Emeritus Professor of Psychology at the University of New Mexico, where he received the University’s Outstanding Graduate Teacher of the Year award for his course on experimental design and analysis, and where he directed the Psychology Honors program for 30 years.
His research interests in applied statistics include methods that accommodate individual differences among people. He received a Fulbright Award from the U.S. Department of State to spend an academic year lecturing in Budapest, Hungary, and continues to offer courses there.
Ken Kelley
Ken Kelley is Professor of Information Technology, Analytics, and Operations and the Associate Dean for Faculty and Research in the Mendoza College of Business at the University of Notre Dame. His work is on quantitative methodology, where he focuses on the development, improvement, and evaluation of statistical methods and measurement issues.
He is an Accredited Professional Statistician (PStat®); recipient of the Anne Anastasi early career award by the Evaluation, Measurement, & Statistics Division of the APA, and previously served as an associate editor of Psychological Methods.
Table of Contents
Appendix (Statistical Tables)
Table 1: Critical Values of t Distribution
Table 2: Critical Values of F Distribution
Table 3: Critical Values of Bonferroni F Distribution With 1 Numerator df and Familywise α of .05
Table 4: Critical Values of Studentized Range Distribution
Table 5: Critical Values of Studentized Maximum Modulus Distribution
Table 6: Critical Values of Dunnett’s Two-Tailed Test for Comparing Treatments to a Control
Table 7: Critical Values of Dunnett’s One-Tailed Test for Comparing Treatments to a Control
Table 8: Critical Values of Bryant-Paulson Generalized Studentized Range
Table 9: Critical Values of Chi-Square Distribution
Table 10: Coefficients of Orthogonal Polynomials
Table 11: Pearson-Hartley Power Charts
References
Name Index
Subject Index
ISBN Information
ISBN: 978-1-138-89228-6 (hbk)
ISBN: 978-1-315-64295-6 (ebk)