
Interrupted Time Series Analysis
Oxford University Press Inc
Published on 24. October 2019
Book
Paperback/Softback
200 pages
978-0-19-094395-0 (ISBN)
Description
Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for building AutoRegressive Integrated Moving Average (ARIMA) impact models. Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection. Not only does the text discuss new developments, including the prospects for widespread adoption of Bayesian hypothesis testing and synthetic control group designs, but it makes optimal use of graphical illustrations in its examples. With forty completed example analyses that demonstrate the implications of model properties, Interrupted Time Series Analysis will be a key inter-disciplinary text in classrooms, workshops, and short-courses for researchers familiar with time series data or cross-sectional regression analysis but limited background in the structure of time series processes and experiments.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
69 black and white line drawings
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 11 mm
Weight
313 gr
ISBN-13
978-0-19-094395-0 (9780190943950)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

David Mcdowall | Richard McCleary | Bradley J. Bartos
Interrupted Time Series Analysis
Book
10/2019
Oxford University Press Inc
€169.80
Shipment within 15-20 days

David Mcdowall | Richard McCleary | Bradley J. Bartos
Interrupted Time Series Analysis
E-Book
09/2019
OUP eBook
€17.49
Available for download

David Mcdowall | Richard McCleary | Bradley J. Bartos
Interrupted Time Series Analysis
E-Book
09/2019
OUP eBook
€17.49
Available for download
Persons
David McDowall is Distinguished Teaching Professor at the University at Albany, State University of New York. He serves on the faculty of Albany's School of Criminal Justice, where he also co-directs the Violence Research Group. His research interests involve the social distribution of criminal violence, including trends and other temporal features in crime rates.
Richard McCleary is a professor at the University of California, Irvine. In addition to faculty appointments in Criminology, Law and Society, Environmental Health Sciences, and Planning, Policy and Design, he directs the Irvine Simulation Modeling Laboratory. His research interests include population forecast models, time series models, and survival models.
Bradley J. Bartos is a doctoral candidate in the Department of Criminology, Law and Society at the University of California, Irvine. Through his work with the Irvine Simulation Modeling Laboratory, he has developed discrete-event population projection models for
various criminal-justice and corrections systems in California. His research interests include mass incarceration, policy evaluation, time series models, and synthetic control group designs.
Richard McCleary is a professor at the University of California, Irvine. In addition to faculty appointments in Criminology, Law and Society, Environmental Health Sciences, and Planning, Policy and Design, he directs the Irvine Simulation Modeling Laboratory. His research interests include population forecast models, time series models, and survival models.
Bradley J. Bartos is a doctoral candidate in the Department of Criminology, Law and Society at the University of California, Irvine. Through his work with the Irvine Simulation Modeling Laboratory, he has developed discrete-event population projection models for
various criminal-justice and corrections systems in California. His research interests include mass incarceration, policy evaluation, time series models, and synthetic control group designs.
Author
Distinguished Teaching ProfessorDistinguished Teaching Professor, School of Criminal Justice, University at Albany, State University of New York
Professor of Criminology, Law, and Society and Planning, Policy and DesignProfessor of Criminology, Law, and Society and Planning, Policy and Design, University of California, Irvine
Ph.D. CandidatePh.D. Candidate, School of Social Ecology at the University of California, Irvine
Content
- List of Figures
- List of Tables
- Acknowledgements
- 1 Introduction to ITSA
- 2 ARIMA Algebra
- 3 The Noise Component: N(at)
- 4 The Intervention Component: X(It)
- 5 Auxiliary Modeling Procedures
- References
- Index