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Design and Analysis of Time-Series Experiments

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Design and Analysis of Time-Series Experiments by Gene V. Glass, Victor L. Willson, and John M. Gottman, is a landmark in experimental methods. It introduces powerful interrupted time-series design...
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  • 14 August 2008
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Hailed as a landmark in the development of experimental methods when it appeared in 1975, Design and Analysis of Time-Series Experiments is available again after several years of being out of print.

Gene V Glass, Victor L. Willson and John M. Gottman have carried forward the design and analysis of perhaps the most powerful and useful quasi-experimental design identified by their mentors in the classic Campbell & Stanley text Experimental and Quasi-experimental Design for Research (1966). In an era when governments seek to resolve questions of experimental validity by fiat and the label 'Scientifically Based Research' is appropriated for only certain privileged experimental designs, nothing could be more appropriate than to bring back the classic text that challenges doctrinaire opinions of proper causal analysis.

Glass, Willson & Gottman introduce and illustrate an armamentarium of interrupted time-series experimental designs that offer some of the most powerful tools for discovering and validating causal relationships in social and education policy analysis. Drawing on the ground-breaking statistical analytic tools of Box & Jenkins, the authors extend the comprehensive autoregressive-integrated-moving-averages (ARIMA) model to accommodate significance testing and estimation of the effects of interventions into real world time-series. Designs and full statistical analyses are richly illustrated with actual examples from education, behavioral psychology, and sociology.

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Price: $61.00
Pages: 264
Publisher: Emerald Publishing Limited
Imprint: Information Age Publishing
Publication Date: 14 August 2008
ISBN: 9781593119805
Format: Paperback
BISACs: SOCIAL SCIENCE / Research, Social research and statistics
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About The Authors.
Introduction To The Republication.
Chapter 1. Time-Series Experiments And The Investigation Of Causal Claims
Chapter 2. Variations On The Basic Time-Series Experimental Design
Chapter 3. Interventions And Intervention Effects
Chapter 4. Sources Of Invalidity In Time-Series Experiments.
Chapter 5. Outline Of Time-Series Analysis.
Chapter 6. Estimating And Testing Intervention Effects.
Chapter 7. Estimating And Testing Intervention Effects In The General Arima (P, D, Q) Model.
Chapter 8. Concomitant Variation In Time-Series Experiments.
Chapter 9. Special Topics In The Analysis Of Time-Series Experiments.
Appendix A. Special Analysis Of Time-Series
Appendix B. Data Lists
Appendix C. Linear Model And Least-Squares Theory
References
Subject Index
Author Index