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Author: David McDowall
Publisher: Oxford University Press
ISBN: 0190943971
Category : Medical
Languages : en
Pages : 201
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Book 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.
Author: David McDowall
Publisher: Oxford University Press
ISBN: 0190943971
Category : Medical
Languages : en
Pages : 201
Get Book Here
Book 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.
Author: David McDowall
Publisher:
ISBN: 0190943947
Category : Business & Economics
Languages : en
Pages : 201
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Book 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.
Author: William R. Shadish
Publisher: Cengage Learning
ISBN:
Category : Education
Languages : en
Pages : 664
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Book Description
Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.
Author: Charles S. Reichardt
Publisher: Guilford Publications
ISBN: 1462540201
Category : Business & Economics
Languages : en
Pages : 382
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Book Description
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
Author: J. C. Barnes
Publisher: John Wiley & Sons
ISBN: 1119110726
Category : Social Science
Languages : de
Pages : 967
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Book Description
Das umfassendste Referenzwerk zu Forschungsdesign und -methoden in Kriminologie und Strafjustiz Die Encyclopedia of Research Methods in Criminology and Criminal Justice bietet einen umfassenden Überblick darüber, welche Forschungsmethoden und statistischen Verfahren in der Kriminologie und den Strafjustizsystemen rund um die Welt bevorzugt zur Anwendung kommen. Das Werk enthält Beiträge von führenden Wissenschaftlern und Fachleuten auf dem Gebiet und vermittelt damit einen gründlichen Einblick in die Techniken, die heutzutage verwendet werden, um drängende Fragen in der Kriminologie und Strafjustiz zu beantworten. Mit den Beiträgen zahlreicher unterschiedlicher Autoren vermittelt die Encyclopedia grundlegende Informationen über Forschungsdesigns, die auf qualitativen und quantitativen Methoden beruhen. Dargestellt werden zudem beliebte Datensätze und die zentralen Quellen staatlicher Statistiken. Zugleich befassen sich die Beiträge mit einem breiten Spektrum an Themen, u.a. mit der neuesten Forschung zum Zusammenhang zwischen Waffen und Kriminalität, der Theorie der rationalen Entscheidung und der Nutzung von Technologien wie der Geodatenkartierung als Mittel zur Verbrechensbekämpfung. Das unverzichtbare Nachschlagewerk bietet: - einen umfassenden Überblick über Forschungsdesign, Forschungsmethoden und statistische Verfahren im internationalen Vergleich - Beiträge von führenden Fachleuten auf dem Gebiet - Daten zur Kriminologie und Strafjustiz von Cambridge bis Chicago - Informationen über die Todesstrafe, häusliche Gewalt, die Kriminalwissenschaft und vieles mehr - Ansätze, um Verbrechen besser zu verstehen, zu erklären und zu verhindern The Encyclopedia of Research Methods in Criminology and Criminal Justice richtet sich an Studierende, Promovierende und Wissenschaftler und ist damit das erste Nachschlagewerk, das einen umfassenden Überblick über dieses wichtige Thema vermittelt.
Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Robert H. Shumway
Publisher:
ISBN: 9781475732627
Category :
Languages : en
Pages : 568
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Book Description
Author: Youseop Shin
Publisher: Univ of California Press
ISBN: 0520293169
Category : Law
Languages : en
Pages : 244
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Book Description
"This book focuses on fundamental elements of time-series analysis that social scientists need to understand to employ time-series analysis for their research and practice. Avoiding extraordinary mathematical materials, this book explains univariate time-series analysis step-by-step, from the preliminary visual analysis through the modeling of seasonality, trends, and residuals to the prediction and the evaluation of estimated models. Then, this book explains smoothing, multiple time-series analysis, and interrupted time-series analysis. At the end of each step, this book coherently provides an analysis of the monthly violent-crime rates as an example."--Provided by publisher.
Author: Lawrence C. Marsh
Publisher: SAGE
ISBN: 9780761924203
Category : Mathematics
Languages : en
Pages : 86
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Book Description
Spline Regression Models shows how to use dummy variables to formulate and estimate spline regression models both in situations where the number and location of the spline knots are known in advance, and where estimation is required.
Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
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Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
