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Paperback. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condizione: new. Paperback. 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. Interrupted Time Series Analysis offers a focused treatment of analytic models and methods for drawing causal inferences from time series. It provides a toolbox for researchers in a number of social science disciplines, including sociology, criminology, political science, psychology, education, and public health where researcher needs to assess the impact of changes in law, policy, and major historical events on behavior, or test and measure the impact oftreatments or interventions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: Brand New. 208 pages. 9.25x6.25x0.50 inches. In Stock.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. Num Pages: 392 pages. BIC Classification: GPS; JHB; JKV; KCH. Category: (G) General (US: Trade). Dimension: 235 x 156. . . . Paperback. . . . .

Condizione: new.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. Num Pages: 392 pages. BIC Classification: GPS; JHB; JKV; KCH. Category: (G) General (US: Trade). Dimension: 235 x 156. . . . Paperback. . . . . Books ship from the US and Ireland.

Paperback. Condizione: Brand New. 1st edition. 368 pages. 9.25x6.25x1.00 inches. In Stock.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Brand New. 1st edition. 368 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand.

Paperback. Condizione: new. Paperback. Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Readers learn not only how-to skills but also the underlying rationales for design features and analytical methods. ARIMA algebra, Box-Jenkins-Tiao models andmodel-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course,with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality, andsynthetic control group designs.Building on the earlier time series books by McCleary and McDowall, Design and Analysis of Time Series Experiments includes recent developments inmodeling, and considers design issues in greater detail than does any existing work. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, the text is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. It will appeal to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference. Design and Analysis of Time Series Experiments develops methods and models for analysis and interpretation of time series experiments. Drawing on examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, it addresses researchers and graduate students in a wide range of the behavioral, biomedical and social sciences. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Readers learn not only how-to skills but also the underlying rationales for design features and analytical methods. ARIMA algebra, Box-Jenkins-Tiao models and model-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course, with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality, and synthetic control group designs. Building on the earlier time series books by McCleary and McDowall, Design and Analysis of Time Series Experiments includes recent developments in modeling, and considers design issues in greater detail than does any existing work. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, the text is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. It will appeal to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference.…

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condizione: new. Hardcover. 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 makesoptimal 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. Interrupted Time Series Analysis offers a focused treatment of analytic models and methods for drawing causal inferences from time series. It provides a toolbox for researchers in a number of social science disciplines, including sociology, criminology, political science, psychology, education, and public health where researcher needs to assess the impact of changes in law, policy, and major historical events on behavior, or test and measure the impact oftreatments or interventions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condizione: new. Hardcover. Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Readers learn not only how-to skills but also the underlying rationales for design features and analytical methods. ARIMA algebra, Box-Jenkins-Tiao models andmodel-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course,with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality, andsynthetic control group designs.Building on the earlier time series books by McCleary and McDowall, Design and Analysis of Time Series Experiments includes recent developments inmodeling, and considers design issues in greater detail than does any existing work. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, the text is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. It will appeal to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference. Design and Analysis of Time Series Experiments develops methods and models for analysis and interpretation of time series experiments. Drawing on examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, it addresses researchers and graduate students in a wide range of the behavioral, biomedical and social sciences. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.