Most books on measurement present a statistical orientation or an orientation toward measurement theory. Although these approaches are valuable, Measurement Error and Research Design is motivated by the lack of literature that enhances understanding of measurement error, its sources, and its effects on responses. This book's purpose is to enhance the design of research, both of measures and of methods.
Author Madhu Viswanathan's work is organized around the meaning of measurement error. It begins with a brief overview of measurement principles supplemented with many examples to provide necessary background to the reader. It analyzes the various causes of different types of measurement error, the nature of responses that would characterize each type of error, and the pattern of empirical outcomes that would be observed. This approach provides guidance in developing and editing items and measures and in designing methods before the fact. It is also perfect for using empirical results to redesign items, measures, and methods. Measurement is treated at a nuts-and-bolts level with concrete examples or errors and empirical procedures.
Measurement Error and Research Design is an ideal text for research methods courses across the social sciences, especially those in which a primer on measurement is needed. For the novice researcher, this book facilitates understanding of the basic principles of measurement required to design measures and methods for empirical research. For the experienced researcher, this book provides an in-depth analysis and discussion of the essence of measurement error and the procedures to minimize it. Most importantly, the book's unique approach bridges measurement and methodology through clear illustrations of the intangibles of scientific research.
An author maintained website, http://www.business.uiuc.edu/~madhuv/msmt.html, features datasets and suggestions for using the book in courses.
"Dr. Viswanathan has made an important contribution to the array of books available on measurement. In his book, he calls the reader's attention to types of errors encountered in measurement, how they are made, and most importantly, how researchers can go about identifying and eliminating them. If you are doing research, whether you are developing measures or using already developed measures, the information in this book will help you to understand how to investigate the limitations of the measures you work with."
—Dennis L. Jackson, University of Windsor, Ontario, Canada
"This book provides a useful systematic introduction to an important and neglected area, that of measurement error in the social sciences. It will prove valuable both to students studying this topic in courses, and to Ph.D. students and researchers starting to carry out social research under their own steam."
—Dougal Hutchison, National Foundation for Educational Research
|What Is Measurement Error?|
|Overview of Traditional Measure Development Procedures|
|Conceptual and Operational Definitions|
|Measure Design and Item Generation|
|Internal Consistency Reliability|
|Dimensionality - Exploratory Factor Analysis|
|Dimensionality - Confirmatory Factor Analysis and Structural Equation Modeling|
|General Issues in Measurement|
|Types of Random and Systematic Error|
|Illustrations of Measurement Error Through Error Patterns|
|Patterns of Responses in Measurement Error|
|Sources of Measurement Error|
|Taxonomy of Error Sources|
|Internal Consistency Reliability Procedures|
|Test-Retest Reliability Procedures|
|Factor Analysis Procedures|
CORRECTED FOR IN MEASURE DEVELOPMENT?
|Guidelines for Identifying and Correcting For Error in Measure Development|
|Generic Issues in Designing Psychometric Tests|
|Item-to-Total Correlations (Internal Consistency Procedures)|
|Test-Retest Correlations (Test-Retest Reliability)|
|Factor Loadings (Exploratory Factor Analysis)|
|Residuals (Confirmatory Factor Analysis)|
|Cross-Construct Correlations (Validity Tests)|
|Conditions of Future Use of Measures|
|Using Internal Consistency and Test-Retest Reliability in Conjunction|
|Using Correlations Across Item-Level Correlations|
|Empirical Assessment of Item-Sequencing Effects|
|Stimulus-Centered Versus Respondent-Centered Scales|
|Formative and Reflective Indicators of Constructs|
ACROSS VARIOUS DISCIPLINES?
|Types of Measures|
|Types of Response Formats|
|Specific Examples of Scales From Different Disciplines|
|Implications for Using Measures in Research Design|
|Implications for Using Structural Equation Modeling|
|Implications for Applied Research|
|Types of Research Designs|
|Measurement Error in Survey Designs|
|Measurement Error in Experimental Designs|
|Research Design and Measurement Error|
|Assumptions of Measurement|
|Qualitative Versus Quantitative Research|
|Measuring the "Measurable"|
|From Physical to Psychological Measurement|
|Ethics in Measurement|
ORIENTATIONS OF THIS BOOK?
|Summary of Chapters|
|Implications for Measurement and Research Design|
|Summary of Orientations|