Spectral Analysis of Time-Series Data

Guilford Publications (Verlag)
  • 1. Auflage
  • |
  • erscheint ca. am 31. Juli 1998
  • Buch
  • |
  • Hardcover
  • |
  • 225 Seiten
978-1-57230-338-6 (ISBN)
This series aims to make statistics and research design more accessible to investigators and students. Each volume offers guidance on how design and theoretical issues affect implementation and interpretation; common errors to avoid; and how to interpret the output from computer program packages.
Provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. Topics covered include research design, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series.
  • Englisch
  • New York
  • |
  • USA
  • Für höhere Schule und Studium
black & white illustrations
  • Höhe: 234 mm
  • |
  • Breite: 162 mm
  • |
  • Dicke: 23 mm
  • 562 gr
978-1-57230-338-6 (9781572303386)
1572303387 (1572303387)
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.
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
"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

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