Spectral Analysis of Time-Series Data: (Methodology in the Social Sciences)

Aimed at those new to the area, and those who have collected time-series data before, this book intends to facilitate the interpretation of observations of behaviour, physiology, mood, perceptual threshold, social indicator variables and other responses. It focuses on practical applications and requires much less mathematical background than many other texts. Using real data sets and the available software (SPSS for Windows), the book employs examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation and potential sources of artefact.

Table of Contents:
Contents 1. Research Questions for Time-Series and Spectral Analysis Studies 2. Issues in Time-Series Research Design, Data Collection, and Data Entry: Getting Started 3. Preliminary Examination of Time-Series Data 4. Harmonic Analysis 5. Periodogram Analysis 6. Spectral Analysis 7. Summary of Issues for Univariate Time-Series Data 8. Assessing Relationships between Two Time Series 9. Cross-Spectral Analysis 10. Applications of Bivariate Time-Series and Cross-Spectral Analyses 11. Pitfalls for the Unwary: Examples of Common Sources of Artifact 12. Theoretical Issues Appendix A. Raw Time-Series Data Appendix B. Critical Values for the Fisher Test of Significance for Periodogram Analysis

About the Author :
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.

Review :
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 Michigan A 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 -