Design and Analysis of TimeSeries Experiments
Nonfiction, Reference & Language, Education & Teaching, Teaching, Statistics, Business & Finance, Economics
| Author: | ISBN: | 9781607528517 | |
| Publisher: | Information Age Publishing | Publication: | October 1, 2008 |
| Imprint: | Information Age Publishing | Language: | English |
| Author: | |
| ISBN: | 9781607528517 |
| Publisher: | Information Age Publishing |
| Publication: | October 1, 2008 |
| Imprint: | Information Age Publishing |
| Language: | English |
Hailed as a landmark in the development of experimental methods when it appeared in 1975, Design and Analysis of TimeSeries 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 quasiexperimental design identified by their mentors in the classic Campbell & Stanley text Experimental and Quasiexperimental 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 timeseries 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 groundbreaking statistical analytic tools of Box & Jenkins, the authors extend the comprehensive autoregressiveintegratedmovingaverages (ARIMA) model to accommodate significance testing and estimation of the effects of interventions into real world timeseries. Designs and full statistical analyses are richly illustrated with actual examples from education, behavioral psychology, and sociology.
Hailed as a landmark in the development of experimental methods when it appeared in 1975, Design and Analysis of TimeSeries 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 quasiexperimental design identified by their mentors in the classic Campbell & Stanley text Experimental and Quasiexperimental 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 timeseries 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 groundbreaking statistical analytic tools of Box & Jenkins, the authors extend the comprehensive autoregressiveintegratedmovingaverages (ARIMA) model to accommodate significance testing and estimation of the effects of interventions into real world timeseries. Designs and full statistical analyses are richly illustrated with actual examples from education, behavioral psychology, and sociology.
