Quasi Experimentation

Quasi Experimentation


  • Release: 2019-08-15
  • Publisher: Guilford Publications
  • Price: FREE
  • File: PDF, 361 page
  • ISBN: 9781462540259
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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.

Doing Quantitative Research in Education with SPSS

Doing Quantitative Research in Education with SPSS


  • Release: 2010-12-10
  • Publisher: SAGE
  • Price: FREE
  • File: PDF, 264 page
  • ISBN: 144624234X
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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.

Experimental and Quasi Experimental Designs for Research

Experimental and Quasi Experimental Designs for Research


  • Release: 2015-09-03
  • Publisher: Ravenio Books
  • Price: FREE
  • File: PDF, 84 page
  • ISBN:
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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.

Experimental and Quasi experimental Designs for Generalized Causal Inference

Experimental and Quasi experimental Designs for Generalized Causal Inference


  • Release: 2002
  • Publisher: Wadsworth Publishing Company
  • Price: FREE
  • File: PDF, 623 page
  • ISBN: UOM:39015061304716
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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.

Quasi Experimental Research Designs

Quasi Experimental Research Designs


  • Release: 2012-02-02
  • Publisher: Oxford University Press
  • Price: FREE
  • File: PDF, 216 page
  • ISBN: 9780199908745
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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.

The SAGE Handbook of Quantitative Methods in Psychology

The SAGE Handbook of Quantitative Methods in Psychology


  • Release: 2009-07-23
  • Publisher: SAGE
  • Price: FREE
  • File: PDF, 800 page
  • ISBN: 9781446206676
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`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

Using Propensity Scores in Quasi Experimental Designs


  • Release: 2013-06-10
  • Publisher: SAGE Publications
  • Price: FREE
  • File: PDF, 360 page
  • ISBN: 9781483310817
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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.

Quasi experimentation

Quasi experimentation


  • Release: 1979
  • Publisher: Wadsworth Publishing Company
  • Price: FREE
  • File: PDF, 405 page
  • ISBN: STANFORD:36105037435018
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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.