- Author : Donald Thomas Campbell
- Publisher :
- Release Date : 1973
- Genre: Experimental design
- Pages : 84
- ISBN 10 : STANFORD:36105004536699
Experimental and Quasi experimental Designs for Research Book Description :
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.
It is usually the case that ethical and pragmatic considerations preclude the use of randomly assigning social work clients to experimental and comparative treatment conditions. In such instances, the practicality of employing a quasi-experimental method becomes an excellent alternative. Quasi-experimental research designs allow researchers to compare groups, and the use of increasingly sophisticated programs provides greater statistical control for what has become the most widely employed research approach used to evaluate the outcomes of social work programs and policies. 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. An introductory chapter describes the valuable role these types of studies have played in social work, from the 1930s to the present. Subsequent chapters delve into each design type's major features, the kinds of questions it is capable of answering, and its strengths and limitations. By linking the theoretical discussion of quasi-experimental designs with actual applications in social work literature, the usefulness and vitality of these research methods comes alive for readers. While this book can be utilized as a manual, it will also have great value 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.
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.
`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 represen
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.
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.
In an era of curricular changes and experiments and high-stakes testing, educational measurement and evaluation is more important than ever. In addition to expected entries covering the basics of traditional theories and methods, other entries discuss important sociopolitical issues and trends influencing the future of that research and practice. Textbooks, handbooks, monographs and other publications focus on various aspects of educational research, measurement and evaluation, but to date, there exists no major reference guide for students new to the field. This comprehensive work fills that gap, covering traditional areas while pointing the way to future developments. Features: Nearly 700 signed entries are contained in an authoritative work spanning four volumes and available in choice of electronic and/or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of education research, measurement, and evaluation to more easily locate directly related entries. (For instance, sample themes include Data, Evaluation, Measurement Concepts & Issues, Research, Sociopolitical Issues, Standards.) Back matter includes a Chronology of the development of the field; a Resource Guide to classic books, journals, and associations; and a detailed Index. Entries conclude with References/Further Readings and Cross References to related entries. The Index, Reader’s Guide themes, and Cross References will combine to provide robust search-and-browse in the e-version.
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.
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, authors W. Alex Edmonds and Thomas D. Kennedy 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.
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.