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Design and Analysis of Time Series Experiments
By Mccleary
0 - Default Title
Description
Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, Design and Analysis of Time Series Experiments is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. Readers learn not only how-to skills but, also the underlying rationales for the design features and the 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 of the authors, Design and Analysis of Time Series Experiments includes more recent developments in modeling, and considers design issues in greater detail than any existing work. Additionally, the book appeals to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference.
Product details
Edition:
1
Number of Pages:
388
Release Date:
2017-06-08
Publication Date:
2014-01-23
Publisher:
ACADEMIC
Languages:
Original:
English
ISBN10:
0190661550
ISBN13:
9780190661557
GPSR Manufacturer Reference:
Weight:
746 g
Height:
161 cm
Width:
240 cm
Thickness:
25 cm
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