Designing Experiments For The Social Sciences

Designing Experiments for the Social Sciences: How to Plan, Create, and Execute Research Using Experiments is a practical, applied text for courses in experimental design. The text assumes that students have just a basic knowledge of the scientific method, and no statistics background is required. With its focus on how to effectively design experiments, rather than how to analyze them, the book concentrates on the stage where researchers are making decisions about procedural aspects of the experiment before interventions and treatments are given. Renita Coleman walks readers step-by-step on how to plan and execute experiments from the beginning by discussing choosing and collecting a sample, creating the stimuli and questionnaire, doing a manipulation check or pre-test, analyzing the data, and understanding and interpreting the results. Guidelines for deciding which elements are best used in the creation of a particular kind of experiment are also given. This title offers rich pedagogy, ethical considerations, and examples pertinent to all social science disciplines.

The first comprehensive guide to natural experiments, providing an ideal introduction for scholars and students.

Laboratory Experiments in the Social Sciences is the only book providing core information for researchers about the ways and means to conduct experiments. Its comprehensive regard for laboratory experiments encompasses “how-to explanations, investigations of philosophies and ethics, explorations of experiments in specific social science disciplines, and summaries of both the history and future of social science laboratories. No other book offers such a direct avenue to enlarging our knowledge in the social sciences. This collection of original chapters combines instructions and advice about the design of laboratory experiments in the social sciences with the array of other issues. While there are books on experimental design and chapters in more general methods books on design, theory, and ethical issues, no other book attempts to discuss the fundamental ideas of the philosophy of science or lays out the methods comprehensively or in such detail. Experimentation has recently prospered because of increasing interest in cross-disciplinary syntheses, and this book of advice, guidelines, and observations underline its potential and increasing importance. · Provides a comprehensive summary of issues in social science experimentation, from ethics to design, management, and financing · Offers "how-to" explanations of the problems and challenges faced by everyone involved in social science experiments · Pays attention to both practical problems and to theoretical and philosophical arguments · Defines commonalities and distinctions within and among experimental situations across the social sciences

Novel collection of essays addressing contemporary trends in political science from a broad spectrum of interdisciplinary scholars.

This book guides you through designing and implementing an online experiment in social science research in a clear and straightforward manner. At an approachable pace, it covers foundational principles of good experimental design before setting out best practice for how to design and conduct web experiments, taking into account the specific methodological challenges of working online with digital tools. The book: Offers practical advice for approaching every stage of the research process Breaks real-world examples into easy to follow steps Focuses on how to make good decisions and choose the right design for your research project This pragmatic guide helps beginner researchers get started with online experiments confidently. It is supported by online resources such as case studies which allow you to see the concepts in practice, and weblinks to tools and resources to aid you.

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.

This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter’s content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and extensive sets of exercises help develop a deeper understanding of the subject. Detailed solutions for some of the exercises and realistic data sets are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.