Hailed as a landmark in the development of experimental methods when itappeared 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.