Interrupted Time Series Analysis
“Interrupted Time Series Analysis” by David McDowall is a concise exploration of ARIMA or Box-Tiao models, published by SAGE in August 1980. This 96-page edition is presented in English and is designed for readers with no statistical background beyond simple correlation. The book focuses on the principles and concepts of ARIMA time series analyses, particularly in the context of interrupted time series quasi-experiments, where a discrete intervention has influenced a social system.
Readers will find a clear exposition of methods for assessing the impact of significant policies or events on continuously observed behaviors. The text aims to provide a foundational understanding of time series analysis, making it accessible for those in fields such as mathematics, probability, statistics, and social science research. This edition serves as a reference for researchers looking to apply these analytical techniques in their work.
Official synopsis Publisher
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 fro
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