Design and Analysis of Time-series Experiments

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IAP, 2008 - Science - 241 pages
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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-movingaverages (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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Contents

ABOUT THE AUTHORS
ix
INTRODUCTION TO THE REPUBLICATION
xi
TIMESERIES EXPERIMENTS AND THE INVESTIGATION OF CAUSAL CLAIMS
1
VARIATIONS ON THE BASIC TIMESERIES EXPERIMENTAL DESIGN
19
INTERVENTIONS AND INTERVENTION EFFECTS
43
SOURCES OF INVALIDITY IN TIMESERIES EXPERIMENTS
53
OUTLINE OF TIMESERIES ANALYSIS
71
ESTIMATING AND TESTING INTERVENTION EFFECTS
119
CONCOMITANT VARIATION IN TIMESERIES EXPERIMENTS
165
SPECIAL TOPICS IN THE ANALYSIS OF TIMESERIES EXPERIMENTS
185
SPECTRAL ANALYSIS OF TIMESERIES
205
DATA LISTS
217
LINEAR MODEL AND LEASTSQUARES THEORY
221
REFERENCES
227
SUBJECT INDEX
235
AUTHOR INDEX
239

ESTIMATING AND TESTING INTERVENTION EFFECTS IN THE GENERAL ARIMA p d q MODEL
151

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About the author (2008)

John M. Gottman is Professor of Psychology at the University of Washington.

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