A comprehensive guide to running randomized impact evaluations of social programs in developing countries This book provides a comprehensive yet accessible guide to running randomized impact evaluations of social programs. Drawing on the experience of researchers at the Abdul Latif Jameel Poverty Action Lab, which has run hundreds of such evaluations in dozens of countries throughout the world, it offers practical insights on how to use this powerful technique, especially in resource-poor environments. This step-by-step guide explains why and when randomized evaluations are useful, in what situations they should be used, and how to prioritize different evaluation opportunities. It shows how to design and analyze studies that answer important questions while respecting the constraints of those working on and benefiting from the program being evaluated. The book gives concrete tips on issues such as improving the quality of a study despite tight budget constraints, and demonstrates how the results of randomized impact evaluations can inform policy. With its self-contained modules, this one-of-a-kind guide is easy to navigate. It also includes invaluable references and a checklist of the common pitfalls to avoid. Provides the most up-to-date guide to running randomized evaluations of social programs, especially in developing countries Offers practical tips on how to complete high-quality studies in even the most challenging environments Self-contained modules allow for easy reference and flexible teaching and learning Comprehensive yet nontechnical

For many applications a randomized algorithm is either the simplest algorithm available, or the fastest, or both. This tutorial presents the basic concepts in the design and analysis of randomized algorithms. The first part of the book presents tools from probability theory and probabilistic analysis that are recurrent in algorithmic applications. Algorithmic examples are given to illustrate the use of each tool in a concrete setting. In the second part of the book, each of the seven chapters focuses on one important area of application of randomized algorithms: data structures; geometric algorithms; graph algorithms; number theory; enumeration; parallel algorithms; and on-line algorithms. A comprehensive and representative selection of the algorithms in these areas is also given. This book should prove invaluable as a reference for researchers and professional programmers, as well as for students.

Using examples and case studies from industry, academia and research literature, Randomized Clinical Trials provides a detailed overview of the key issues involved in designing, conducting, analysing and reporting randomized clinical trials. It examines the methodology for conducting Phase III clinical trials, developing the protocols, the practice for capturing, measuring, and analysing the resulting clinical data and their subsequent reporting. Randomized clinical trials are the principal method for determining the relative efficacy and safety of alternative treatments, interventions or medical devices. They are conducted by groups comprising one or more of pharmaceutical and allied health-care organisations, academic institutions, and charity supported research groups. In many cases such trials provide the key evidence necessary for the regulatory approval of a new product for future patient use. Randomized Clinical Trials provides comprehensive coverage of such trials, ranging from elementary to advanced level. Written by authors with considerable experience of clinical trials, Randomized Clinical Trials is an authoritative guide for clinicians, nurses, data managers and medical statisticians involved in clinical trials research and for health care professionals directly involved in patient care in a clinical trial context.

Randomized response is a data collection strategy specifically designed for surveys of a sensitive nature. By establishing a probabilistic connection between question and answer, randomized response and related methods protect respondents who are asked to disclose personal information. Covering a half century of theoretical and applied research, the Second Edition of James Alan Fox’s Randomized Response and Related Methods significantly updates and expands what was, at the time, the first comprehensive and practical guide to randomized response.

Systematically teaches key paradigmic algorithm design methods Provides a deep insight into randomization

The material in this work is organized in such as way as to illustrate how randomization tests are related to topics in parametric and traditional nonparametric statistics. The work extends the scope of applications by freeing tests from parametric assumptions without reducing data to ranks. This edition provides many new features, including more accessible terminology to clarify understanding, a current analysis of single-unit experiments as well as single-subject experiments, a discussion on how single-subject experiments relate to repeated-measures experiments and the use of randomized tests in single-patient research, and more.

Moving on from earlier stochastic and robust control paradigms, this book introduces the fundamentals of probabilistic methods in the analysis and design of uncertain systems. The use of randomized algorithms, guarantees a reduction in the computational complexity of classical robust control algorithms and in the conservativeness of methods like H-infinity control. Features: • self-contained treatment explaining randomized algorithms from their genesis in the principles of probability theory to their use for robust analysis and controller synthesis; • comprehensive treatment of sample generation, including consideration of the difficulties involved in obtaining independent and identically distributed samples; • applications in congestion control of high-speed communications networks and the stability of quantized sampled-data systems. This monograph will be of interest to theorists concerned with robust and optimal control techniques and to all control engineers dealing with system uncertainties.