Spectral Analysis of Time-Series Data

Rebecca M. Warner, PhD, is Professor of Psychology at the University of New Hampshire. Her research interests include communication style, cardiovascular reactivity and modulation of physiological rhythms in social interactions, and coordination of talk patterns in conversation.

This is an excellent book for behavioral and social scientists seeking a quick but thorough introduction to spectral analysis. Rigorous in presenting basic equations, it also features practical examples that facilitate the learning process. The author's clear exposition and use of commonly accessible software to illustrate analyses will help readers make the leap from reading this book to actually analyzing their own time-series data. --Randy J. Larsen, PhD, Department of Psychology, University of MichiganA wonderful book, filled with clear language and interesting examples. Warner helps us understand how many of the enduring features of life are repetitive ones that cannot be described in terms of means and static relationships. A common-sense guide to cyclical patterns in time-series data, the volume is both practical and intellectually stimulating. --James M. Dabbs, PhD, Department of Psychology, Georgia State University -

• Contents1. Research Questions for Time-Series and Spectral Analysis Studies2. Issues in Time-Series Research Design, Data Collection, and Data Entry: Getting Started3. Preliminary Examination of Time-Series Data4. Harmonic Analysis5. Periodogram Analysis6. Spectral Analysis7. Summary of Issues for Univariate Time-Series Data8. Assessing Relationships between Two Time Series9. Cross-Spectral Analysis10. Applications of Bivariate Time-Series and Cross-Spectral Analyses11. Pitfalls for the Unwary: Examples of Common Sources of Artifact12. Theoretical IssuesAppendix A. Raw Time-Series DataAppendix B. Critical Values for the Fisher Test of Significance for Periodogram Analysis