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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: 27 May 2022

Into the Future

Into the Future

Chapter:
(p.154) 6 Into the Future
Source:
Interrupted Time Series Analysis
Author(s):

David McDowall

Richard McCleary

Bradley J. Bartos

Publisher:
Oxford University Press
DOI:10.1093/oso/9780190943943.003.0006

Chapter 6 introduces two conceptual issues that, in our opinion, will become important in the near future. The first involves the validity of statistical inference. Critics of the conventional null hypothesis significance test generally focus on the undue influence of sample size on p-values and the common misinterpretation of significance levels. Bayesian approaches address and, to some extent, solve both shortcomings. The second conceptual issue involves the use of control time series. As a rule, valid causal inferences require the use of a contrasting control time series. In most instances, no ideal control series is available; however, a synthetic ideal control series can sometimes be constructed from an ensemble of less-than-ideal control time series.

Keywords:   Counterfactual, Synthetic Control, SUTVA, placebo test, robustness, manipulation, natural experiment, random assignment, interference

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