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Interrupted Time Series Analysis$
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David McDowall, Richard McCleary, and Bradley J. Bartos

Print publication date: 2019

Print ISBN-13: 9780190943943

Published to Oxford Scholarship Online: February 2021

DOI: 10.1093/oso/9780190943943.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use.date: 28 May 2022

Introduction to ITSA

Introduction to ITSA

(p.1) 1 Introduction to ITSA
(p.v) Interrupted Time Series Analysis

David McDowall

Richard McCleary

Bradley J. Bartos

Oxford University Press

Chapter 1 introduces Interrupted Time Series Analysis (ITSA) as a toolbox for researchers whose data consist of a long sequence of observations | say, N ≥15 observations | measured before and after a treatment or intervention. Sometimes the treatment or intervention is implemented by the researcher, other times it occurs naturally or by accident. The chapter also describes a family of impact types, characterized by their onset (abrupt or gradual) and duration (permanent or temporary); and the essential role of counterfactual controls in causal inference. The chapter concludes with an outline and summary of the book's subsequent chapters.

Keywords:   time series, quasi-experiment, causal inference, cook & Campbell, pretest-postest, internal validity, statistical conclusion validity, counterfactual, synthetic control

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