This book, first published in English in 1932, serves as an introduction to experimental embryology. This title, while covering in-depth the field of investigation, presents the general issues surrounding this particular study rather than just providing an analysis of particular results. This title will be of interest to students of introductory biology and the history of science.

Discussions of the use and limits of randomized control trials, considering the power of theory, external validity, gaps in knowledge, and what issues matter. The practice of development economics has undergone something of a revolution as many economists have adopted new methods to answer perennial questions about the effectiveness of anti-poverty programs. In this book, prominent development economists discuss the use and impact of one of the most significant of these new methods, randomized control trials (RCTs) and field experiments. In extended interviews conducted over a period of several years, they explain their work and their thinking and consider the broader issues of how we learn about the world and how we can change it for the better. These conversations offer specialists and nonspecialists alike a unique opportunity to hear economists speak in their own words, free of the confines of a particular study or econometric esoterica. The economists describe how they apply research findings in the way they think about the world, revealing their ideas about the power of theory, external validity, gaps in knowledge, and what issues matter. Also included are interviews with RCT observers, critics, sponsors, consumers, and others. Each interview provides a brief biography of the interviewee. Thorough annotations offer background and explanations for key ideas and studies referred to in the conversations. Contributors Abhijit Banerjee, Nancy Birdsall, Chris Blattman, Alex Counts, Tyler Cowen, Angus Deaton, Frank DeGiovanni, Esther Duflo, Pascaline Dupas, Xavi Gine, Rachel Glennerster, Judy Gueron, Elie Hassenfeld, Dean Karlan, Michael Kremer, David McKenzie, Jonathan Morduch, Lant Pritchett, Jonathan Robinson, Antoinette Schoar, Dean Yang

This book provides researchers, students, and practitioners with a methodology to evaluate the impacts of a wide diversity of development projects and policies on local economies. Projects and policies often create spillovers within project areas. LEWIE uses simulation methods to quantify these spillovers. It has become a complement to randomized control trials (RCTs), as governments and donors become interested in documenting impacts beyond the treated, comparing the likely impacts of alternative interventions, and designing complementary interventions to influence program and policy impacts. It is also a tool for impact evaluation where RCTs are not feasible. Chapters 1-4 motivate and present the basics of impact simulation, including how to design a LEWIE model, how to estimate the model, and how to obtain the necessary data. The remaining chapters provide a diversity of interesting real-world applications and extensions of the basic models. The applications include evaluations of the impacts of cash transfers for the poor, ecotourism, global food-price shocks, irrigation projects, migration, and corruption. Each chapter provide readers with the tools they need to conduct their own local economy-wide impact evaluations. All models and data used in this book are available on-line.

Once primarily used in medical clinical trials, random assignment experimentation is now accepted among social scientists across a broad range of disciplines. The technique has been used in social experiments to evaluate a variety of programs, from microfinance and welfare reform to housing vouchers and teaching methods. How did randomized experiments move beyond medicine and into the social sciences, and can they be used effectively to evaluate complex social problems? Fighting for Reliable Evidence provides an absorbing historical account of the characters and controversies that have propelled the wider use of random assignment in social policy research over the past forty years. Drawing from their extensive experience evaluating welfare reform programs, noted scholar practitioners Judith M. Gueron and Howard Rolston portray randomized experiments as a vital research tool to assess the impact of social policy. In a random assignment experiment, participants are sorted into either a treatment group that participates in a particular program, or a control group that does not. Because the groups are randomly selected, they do not differ from one another systematically. Therefore any subsequent differences between the groups can be attributed to the influence of the program or policy. The theory is elegant and persuasive, but many scholars worry that such an experiment is too difficult or expensive to implement in the real world. Can a control group be truly insulated from the treatment policy? Would staffers comply with the random allocation of participants? Would the findings matter? Fighting for Reliable Evidence recounts the experiments that helped answer these questions, starting with the income maintenance experiments and the Supported Work project in the 1960s and 1970s. Gueron and Rolston argue that a crucial turning point came during the 1980s, when Congress allowed states to experiment with welfare programs and foundations, states, and the federal government funded larger randomized trials to assess the impact of these reforms. As they trace these historical shifts, Gueron and Rolston discuss the ways that strategies for resolving theoretical and practical problems were developed, and they highlight the strict conditions required to execute a randomized experiment successfully. What emerges is a nuanced portrait of the potential and limitations of social experiments to advance empirical knowledge. Weaving history, data analysis and personal experience, Fighting for Reliable Evidence offers valuable lessons for researchers, policymakers, funders, and informed citizens interested in isolating the effect of policy initiatives. It is an essential primer on welfare policy, causal inference, and experimental designs.

This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.

Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize various design options Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments.

Experimental design is one of the most fundamental topics in social science statistics. This book introduces the reader to the elements of experimental design and analysis through careful explanations of the procedures as well as through illustrations using actual examples.

This book summarizes the main methods of experimental stress analysis and examines their application to various states of stress of major technical interest, highlighting aspects not always covered in the classic literature. It is explained how experimental stress analysis assists in the verification and completion of analytical and numerical models, the development of phenomenological theories, the measurement and control of system parameters under operating conditions, and identification of causes of failure or malfunction. Cases addressed include measurement of the state of stress in models, measurement of actual loads on structures, verification of stress states in circumstances of complex numerical modeling, assessment of stress-related material damage, and reliability analysis of artifacts (e.g. prostheses) that interact with biological systems. The book will serve graduate students and professionals as a valuable tool for finding solutions when analytical solutions do not exist.