Download or read book Causal Models in Experimental Designs written by H. M. Blalock and published by Routledge. This book was released on 2017-07-12 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a companion volume to Causal Models in the Social Sciences, the majority of articles concern panel designs involving repeated measurements while a smaller cluster involve discussions of how experimental designs may be improved by more explicit attention to causal models. All of the papers are concerned with complications that may occur in actual research designs- as compared with idealized ones that often become the basis of textbook discussions of design issues.

Download or read book Causal Models in Panel and Experimental Designs written by Hubert M. Blalock and published by Aldine De Gruyter. This book was released on 1985 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Causal Models in Experimental Designs written by Hubert M. Blalock and published by Transaction Publishers. This book was released on 2017 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a companion volume to the Causal Models in the Social Sciences, the majority of articles concern panel designs involving repeated measurements while a smaller cluster involves discussions of how experimental designs may be improved by more explicit attention to causal models. All of the papers are concerned with complications that may occur in actual research designs--as compared with idealized ones that often become the basis of textbook discussions of design issues. In thinking about the revision of that volume, considerable literature has accumulated. As a result, this volume attempts to bridge the gap in time and substance to that earlier effort. Blalock examined articles that seemed to hold the most promise of expanding the variety of topics in research methods to the causal modeling approach, and addressing the design issues involved. The majority of these fell under the heading of panel designs involving repeated measurements; a smaller cluster involved discussions of how our understanding of experimental designs could be improved by paying explicit attention to causal models. Blalock presented five chapters bearing on experimental designs into Part I, since the issues with which they deal are more general than those that treat more specifically with the handling of change data. Although many readers may have more immediate interest in these latter papers, which appear in Part II, Blalock thought it wise to encourage such readers to examine broader issues before plunging specifically into discussions of panel designs. H.M. Blalock, Jr. (1926-1991) was professor of sociology at the University of Washington, Seattle. He was recipient of the 1973 ASA Samuel Stouffer Prize, and was a Fellow of the American Statistical Association and the American Academy of Arts and Sciences, and is a member of the National Academy of Sciences. He was the 70th president of the American Sociological Association.

Download or read book Blalock H Causal Models in Panel and Experimental Design written by Cresta Booksellers Direct and published by . This book was released on 1985 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Experimental and Quasi experimental Designs for Generalized Causal Inference written by William R. Shadish and published by Cengage Learning. This book was released on 2002 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Experiments in Public Management Research written by Oliver James and published by Cambridge University Press. This book was released on 2017-07-27 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of experimental research and methods in public management, and their impact on theory, research practices and substantive knowledge.

Download or read book Causal Models in the Social Sciences written by H. M. Blalock, Jr. and published by Transaction Publishers. This book was released on 2011-12-31 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This collection of articles is a course book on the causal modeling approach to theory construction and data analysis. H. M. Blalock, Jr. summarizes the then-current developments in causal model utilization in sociology, political science, economics, and other disciplines. This book provides a comprehensive multidisciplinary picture of the work on causal models. It seeks to address the problem of measurement in the social sciences and to link theory and research through the development of causal models. Organized into five sections (Simple Recursive Models, Path Analysis, Simultaneous Equations Techniques, The Causal Approach to Measurement Error, and Other Complications), this volume contains twenty-seven articles (eight of which were specially commissioned). Each section begins with an introduction explaining the concepts to be covered in the section and links them to the larger subject. It provides a general overview of the theory and application of causal modeling. Blalock argues for the development of theoretical models that can be operationalized and provide verifiable predictions. Many of the discussions of this subject that occur in other literature are too technical for most social scientists and other scholars who lack a strong background in mathematics. This book attempts to integrate a few of the less technical papers written by econometricians such as Koopmans, Wold, Strotz, and Fisher with discussions of causal approaches in the social and biological sciences. This classic text by Blalock is a valuable source of material for those interested in the issue of measurement in the social sciences and the construction of mathematical models.

Download or read book Best Practices in Quantitative Methods written by Jason W. Osborne and published by SAGE. This book was released on 2008 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Download or read book Estimating Causal Effects written by Barbara Schneider and published by . This book was released on 2007 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the value of quasi-experimental techniques that can be used to approximate randomized experiments. The goal is to describe the logic of causal inference for researchers and policymakers who are not necessarily trained in experimental and quasi-experimental designs and statistical techniques.

Download or read book Causality and Causal Modelling in the Social Sciences written by Federica Russo and published by Springer Science & Business Media. This book was released on 2008-09-18 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science.

Download or read book Design and Analysis of Time Series Experiments written by Richard McCleary and published by Oxford University Press. This book was released on 2017-05-11 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistics And Experimental Design For Psychologists A Model Comparison Approach written by Rory Allen and published by World Scientific Publishing Company. This book was released on 2017-08-28 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook for psychologists which combines the model comparison method in statistics with a hands-on guide to computer-based analysis and clear explanations of the links between models, hypotheses and experimental designs. Statistics is often seen as a set of cookbook recipes which must be learned by heart. Model comparison, by contrast, provides a mental roadmap that not only gives a deeper level of understanding, but can be used as a general procedure to tackle those problems which can be solved using orthodox statistical methods.Statistics and Experimental Design for Psychologists focusses on the role of Occam's principle, and explains significance testing as a means by which the null and experimental hypotheses are compared using the twin criteria of parsimony and accuracy. This approach is backed up with a strong visual element, including for the first time a clear illustration of what the F-ratio actually does, and why it is so ubiquitous in statistical testing.The book covers the main statistical methods up to multifactorial and repeated measures, ANOVA and the basic experimental designs associated with them. The associated online supplementary material extends this coverage to multiple regression, exploratory factor analysis, power calculations and other more advanced topics, and provides screencasts demonstrating the use of programs on a standard statistical package, SPSS.Of particular value to third year undergraduate as well as graduate students, this book will also have a broad appeal to anyone wanting a deeper understanding of the scientific method.

Download or read book Correlation and Causality written by David A. Kenny and published by John Wiley & Sons. This book was released on 1979 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural modeling; Covariance algebra; Principles of path analysis; Models with observed variables as causes; Measurement error in the exogenous variable and third variables; Observed variables as causes of each other; Single unmeasured exogenous variables; Causal models with multiple unmeasured variables; Causal models with unmeasured variables; Causal models and true experiments; The nonequivalent control group design; Cross-lagged panel correlation; Loose ends.

Download or read book Experimental Political Science and the Study of Causality written by Rebecca B. Morton and published by Cambridge University Press. This book was released on 2010-08-06 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, political scientists use the term 'experiment' or 'experimental' to describe their empirical research. One of the primary reasons for doing so is the advantage of experiments in establishing causal inferences. In this book, Rebecca B. Morton and Kenneth C. Williams discuss in detail how experiments and experimental reasoning with observational data can help researchers determine causality. They explore how control and random assignment mechanisms work, examining both the Rubin causal model and the formal theory approaches to causality. They also cover general topics in experimentation such as the history of experimentation in political science; internal and external validity of experimental research; types of experiments - field, laboratory, virtual, and survey - and how to choose, recruit, and motivate subjects in experiments. They investigate ethical issues in experimentation, the process of securing approval from institutional review boards for human subject research, and the use of deception in experimentation.

Download or read book Experimental Design for Optimal Shift Intervention in Causal Model written by Jiaqi Zhang (Machine learning researcher) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transforming a causal system from a given initial state to a desired target state is an important task permeating multiple fields including control theory, biology, and materials science. In causal models, such transformations can be achieved by performing a set of interventions. When the space of possible interventions is large, making an exhaustive search infeasible, experimental design strategies are needed. In this context, encoding the causal relationships between the variables, and thus the effect of interventions on the system, is critical in order to identify desirable interventions more efficiently. In this thesis, we develop an iterative causal method to identify optimal interventions, as measured by the discrepancy between the post-interventional mean of the distribution and a desired target mean. We formulate an active learning strategy that uses the samples obtained so far from different interventions to update the belief about the underlying causal model, as well as to identify the samples that are most informative about optimal interventions and thus should be acquired in the next batch. The approach employs a Bayesian update for the causal model and prioritizes informative interventions using a carefully designed, causally informed acquisition function. Moreover, the introduced acquisition function is evaluated in closed form, allowing for efficient optimization. The resulting algorithms are also theoretically grounded with information-theoretic bounds and provable consistency results. We illustrate the method on both synthetic data and real-world biological data, more precisely gene expression data from Perturb-CITE-seq experiments. In this case the goal is to identify optimal perturbations to induce a specific cell state transition; the proposed causal approach is observed to achieve better sample efficiency compared to several baselines. In both cases we observe that the causally informed acquisition function notably outperforms existing criteria allowing for optimal intervention design with significantly less experiments.

Download or read book The Experimental Side of Modeling written by Isabelle F. Peschard and published by U of Minnesota Press. This book was released on 2018-10-02 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: An innovative, multifaceted approach to scientific experiments as designed by and shaped through interaction with the modeling process The role of scientific modeling in mediation between theories and phenomena is a critical topic within the philosophy of science, touching on issues from climate modeling to synthetic models in biology, high energy particle physics, and cognitive sciences. Offering a radically new conception of the role of data in the scientific modeling process as well as a new awareness of the problematic aspects of data, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Contributors address such issues as the construction of models in conjunction with scientific experimentation; the status of measurement and the function of experiment in the identification of relevant parameters; how the phenomena under study are reconceived when accounted for by a model; and the interplay between experimenting, modeling, and simulation when results do not mesh. Highlighting the mediating role of models and the model-dependence (as well as theory-dependence) of data measurement, this volume proposes a normative and conceptual innovation in scientific modeling—that the phenomena to be investigated and modeled must not be precisely identified at the start but specified during the course of the interactions arising between experimental and modeling activities. Contributors: Nancy D. Cartwright, U of California, San Diego; Anthony Chemero, U of Cincinnati; Ronald N. Giere, U of Minnesota; Jenann Ismael, U of Arizona; Tarja Knuuttila, U of South Carolina; Andrea Loettgers, U of Bern, Switzerland; Deborah Mayo, Virginia Tech; Joseph Rouse, Wesleyan U; Paul Teller, U of California, Davis; Michael Weisberg, U of Pennsylvania; Eric Winsberg, U of South Florida.

Download or read book Design and Analysis of Experiments and Observational Studies using R written by Nathan Taback and published by CRC Press. This book was released on 2022-03-10 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design, data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected. Features: Classical experimental design with an emphasis on computation using tidyverse packages in R. Applications of experimental design to clinical trials, A/B testing, and other modern examples. Discussion of the link between classical experimental design and causal inference. The role of randomization in experimental design and sampling in the big data era. Exercises with solutions. Instructor slides in RMarkdown, a new R package will be developed to be used with book, and a bookdown version of the book will be freely available. The proposed book will emphasize ethics, communication and decision making as part of design, data analysis, and statistical thinking.