Your Book is AVAILABLE NOW !!!
Experimental And Quasi
There are many choices of the "Experimental And Quasi" Pdf, ePub, Mobi and Audiobook. You can Read and Download as much as you want after registering for FREE.
|Author||: Charles S. Reichardt|
|Editor||: Guilford Publications|
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. Comparing quasi-experiments to randomized experiments, Reichardt discusses when and why the former might be a better choice than the latter in the face of the contingencies that are likely to arise in practice. Modern methods 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. Adding to its discussion of prototypical quasi-experiments, the book also provides a complete typology of quasi-experimental design options to help the reader craft the best research design to fit the circumstances of a given study.
|Author||: Donald Thomas Campbell,Julian C. Stanley|
|Author||: Donald T. Campbell,Julian C. Stanley|
|Editor||: Ravenio Books|
We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
|Author||: WS. SHADISH,William R. Shadish,Thomas D. Cook,Donald Thomas Campbell|
|Editor||: Wadsworth Publishing Company|
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||: Daniel Muijs|
This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book's website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.
|Author||: Donald Thomas Campbell,Julian C. Stanley|
|Author||: Bruce A. Thyer|
|Editor||: Oxford University Press|
This pocket guide describes the logic, design, and conduct of the range of such designs, encompassing pre-experiments, quasi-experiments making use of a control or comparison group, and time-series designs. While it can be utilized as a manual, this book is also valuable for practitioners seeking a greater conceptual understanding of quasi-experimental studies in social work literature. Human service professionals planning to undertake a program evaluation of their agency's services will find this book helpful in understanding the steps and actions needed to adopt a quasi-experimental strategy.
|Author||: William R. Shadish,Thomas D. Cook,Donald Thomas Campbell|
This successor of the original Cook/Campbell Quasi-Experimentation: Design and Analysis Issues for Field Settings represents updates in the field over the last two decades. The book covers four major topics in field experimentation: Theoretical matters: Experimentation, causation, and validity ; Quasi-experimental design: Regression discontinuity designs, interrupted time series designs, quasi-experimental designs that use both pretests and control groups, and other designs ; Randomized experiments: Logic and design issues, and practical problems involving ethics, recruitment, assignment, treatment implementation, and attrition ; Generalized causal inference: A grounded theory of generalized causal inference, along with methods for implementing that theory in single and multiple studies.
|Author||: William M. Holmes|
|Editor||: SAGE Publications|
Using Propensity Scores in Quasi-Experimental Designs, by William M. Holmes, examines how propensity scores can be used to reduce bias with different kinds of quasi-experimental designs and to fix or improve broken experiments. Requiring minimal use of matrix and vector algebra, the book covers the causal assumptions of propensity score estimates and their many uses, linking these uses with analysis appropriate for different designs. Thorough coverage of bias assessment, propensity score estimation, and estimate improvement is provided, along with graphical and statistical methods for this process. Applications are included for analysis of variance and covariance, maximum likelihood and logistic regression, two-stage least squares, generalized linear regression, and general estimation equations. The examples use public data sets that have policy and programmatic relevance across a variety of disciplines.
|Author||: Roger E Millsap,Alberto Maydeu-Olivares|
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.
|Author||: Thomas D. Cook,Donald Thomas Campbell|
|Editor||: Wadsworth Publishing Company|
This book presents some quasi-experimental designs and design features that can be used in many social research settings. The designs serve to probe causal hypotheses about a wide variety of substantive issues in both basic and applied research. Each design is assessed in terms of four types of validity, with special stress on internal validity. Although general conclusions are drawn about the strengths and limitations of each design, emphasis is also placed on the fact that the relevant threats to valid inference are specific to each research setting. Consequently, a threat that is usually associated with a particular design need not invariably be associated with that design.
|Author||: Sarah Boslaugh,Louise-Anne McNutt|
The Encyclopedia of Epidemiology presents state-of-the-art information from the field of epidemiology in a less technical and accessible style and format. With more than 600 entries, no single reference provides as comprehensive a resource in as focused and appropriate manner. The entries cover every major facet of epidemiology, from risk ratios to case-control studies to mediating and moderating variables, and much more. Relevant topics from related fields such as biostatistics and health economics are also included.
|Author||: W. Alex Edmonds,Thomas D. Kennedy|
|Editor||: SAGE Publications|
The Second Edition of An Applied Guide to Research Designs offers researchers in the social and behavioral sciences guidance for selecting the most appropriate research design to apply in their study. Using consistent terminology, the authors visually present a range of research designs used in quantitative, qualitative, and mixed methods to help readers conceptualize, construct, test, and problem solve in their investigation. The Second Edition features revamped and expanded coverage of research designs, new real-world examples and references, a new chapter on action research, and updated ancillaries.
|Author||: Jim McKinley,Heath Rose|
The Routledge Handbook of Research Methods in Applied Linguistics provides a critical survey of the methodological concepts, designs, instruments and types of analysis that are used within the broad field of applied linguistics. With more than 40 chapters written by leading and emerging scholars, this book problematizes and theorizes applied linguistics research, incorporating numerous multifaceted methodological considerations and pointing to the future of good practice in research. Topics covered include: key concepts and constructs in research methodology, such as sampling strategies and mixed methods research; research designs such as experimental research, case study research, and action research; data collection methods, from questionnaires and interviews to think-aloud protocols and data elicitation tasks; data analysis methods, such as use of R, inferential statistical analysis, and qualitative content analysis; current considerations in applied linguistics research, such as a need for transparency and greater incorporation of multilingualism in research; and recent innovations in research methods related to multimodality, eye-tracking, and advances in quantitative methods. The Routledge Handbook of Research Methods in Applied Linguistics is key reading for both experienced and novice researchers in Applied Linguistics as well as anyone undertaking study in this area.
|Author||: Bruce Thyer|
In the field of social work, qualitative research is starting to gain more prominence as are mixed methods and various issues regarding race, ethnicity and gender. These changes in the field are reflected and updated in The Handbook of Soical Work Research Methods, Second Edition. This text contains meta analysis, designs to evaluate treatment and provides the support to help students harness the power of the Internet. This handbook brings together leading scholars in research methods in social work.
|Author||: Steven Durlauf,L. Blume|
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
|Author||: William Outhwaite,Stephen Turner|
"An excellent guidebook through different approaches to social science measurement, including the all-important route-maps that show us how to get there." - Roger Jowell, City University "In this wide-ranging collection of chapters, written by acknowledged experts in their fields, Outhwaite and Turner have brought together material in one volume which will provide an extremely important platform for consideration of the full range of contemporary analytical and methodological issues." - Charles Crothers, Auckland University of Technology This is a jewel among methods Handbooks, bringing together a formidable collection of international contributors to comment on every aspect of the various central issues, complications and controversies in the core methodological traditions. It is designed to meet the needs of those disciplinary and nondisciplinary problem-oriented social inquirers for a comprehensive overview of the methodological literature. The text is divided into 7 sections: Overviews of methodological approaches in the social sciences Cases, comparisons and theory Quantification and experiment Rationality, complexity and collectivity Interpretation, critique and postmodernity Discourse construction Engagement. Edited by two leading figures in the field, the Handbook is a landmark work in the field of research methods. More than just a 'cookbook' that teaches readers how to master techniques, it will give social scientists in all disciplines an appreciation for the full range of methodological debates today, from the quantitative to the qualitative, giving them deeper and sharpen insights into their own research questions. It will generate debate, solutions and a series of questions for researchers to exploit and develop in their research and teaching.
|Author||: Sharlene Nagy Hesse-Biber,R. Burke Johnson|
|Editor||: Oxford University Press|
Offering a variety of innovative methods and tools, The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry provides the most comprehensive and up-to-date presentation on multi- and mixed-methods research available. Written in clear and concise language by leading scholars in the field, it enhances and disrupts traditional ways of asking and addressing complex research questions. Topics include an overview of theory, paradigms, and scientific inquiry; a guide to conducting a multi- and mixed-methods research study from start to finish; current uses of multi- and mixed-methods research across academic disciplines and research fields; the latest technologies and how they can be incorporated into study design; and a presentation of multiple perspectives on the key remaining debates. Each chapter in the volume is structured to include state-of-the-art research examples that cross a range of disciplines and interdisciplinary research settings. In addition, the Handbook offers multiple quantitative and qualitative theoretical and interdisciplinary visions and praxis. Researchers, faculty, graduate students, and policy makers will appreciate the exceptional, timely, and critical coverage in this Handbook, which deftly addresses the interdisciplinary and complex questions that a diverse set of research communities are facing today.
|Author||: Jason W. Osborne|
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.
|Author||: Bradley Huitema|
|Editor||: John Wiley & Sons|
A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.