Interrupted Time Series Analysis

Interrupted Time Series Analysis

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Description

Describes ARIMA or Box Tiao models, widely used in the analysis of interupted time series quasi-experiments, assuming no statistical background beyond simple correlation. The principles and concepts of ARIMA time series analyses are developed and applied where a discrete intervention has impacted a social system.



'...this is the kind of exposition I wished I had had some ten years ago when venturing into the world of autoregressive, moving-average (ARIMA) models of time-series analysis...This monograph nicely lays out a method for assessing the impact of a discrete policy or event of some importance on behavior which can be continuously observed...If widely used, as I hope, it will save a generation of social scientists from the labor of having to learn this methodology the hard way...' -- Helmut Norpoth, State University of New York
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Product details

  • Paperback | 96 pages
  • 139 x 215 x 5.84mm | 140g
  • Thousand Oaks, United States
  • English
  • Expanded
  • 0803914938
  • 9780803914933
  • 1,137,286

About David McDowall

David McDowall is editor of the Journal of Quantitative Criminology. He also is co-director of the Violence Research Group, a collaborative research effort that studies patterns of interpersonal violence.

Professor McDowall is especially interested in time series analysis of patterns in crime and violence. His recent research includes an evaluation of the preventive effects of juvenile curfew laws on youth crime, studies of defensive firearm use, and an examination of disagreements between homicide data sources.
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