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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.
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.
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
This book constitutes the joint refereed proceedings of the 11th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2008 and the 12th International Workshop on Randomization and Computation, RANDOM 2008, held in Boston, MA, USA, in August 2008. The 20 revised full papers of the APPROX 2008 workshop were carefully reviewed and selected from 42 submissions and focus on algorithmic and complexity issues surrounding the development of efficient approximate solutions to computationally difficult problems. RANDOM 2008 is concerned with applications of randomness to computational and combinatorial problems and accounts for 27 revised full papers, also diligently reviewed and selected out of 52 workshop submissions.
Pragmatic Randomized Clinical Trials Using Primary Data Collection and Electronic Health Records addresses the practical aspects and challenges of the design, implementation, and dissemination of pragmatic randomized trials, also sometimes referred to as practical or hybrid randomized trials. While less restrictive and more generalizable than traditional randomized controlled trials, such trials have specific challenges which are addressed in this book. The book contains chapters encompassing common designs along with advantages and limitations of such designs, analytic aspects in planning trials and estimating sample size, and how to use patient partners to help design and operationalize pragmatic randomized trials. Pragmatic trials conducted using primary data collection and trials embedded in electronic health records - including electronic medical records and administrative insurance claims - are addressed. This comprehensive resource is valuable not only for pharmacoepidemiologists, biostatisticians and clinical researchers, but also across the biomedical field for those who are interested in applying pragmatic randomized clinical trials in their research. Addresses typical designs and challenges of pragmatic randomized clinical trials (pRCTs) Encompasses analytic aspects of such trials Discusses real cases on operational challenges in launching and conducting pRCTs in electronic health records
This book constitutes the refereed proceedings of the Third International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM'99, held jointly with the Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX'99, in Berkeley, California in August 1999. The volume presents 24 revised full papers selected from 44 submissions and four invited contributions. The papers present a wealth of new results and document the state-of-the-art in the areas covered by the workshop.
Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly. Far too often the subtle nuances that distinguish proper randomization from flawed randomization are completely ignored in trial reports that state only that randomization was used, with no additional information. Experience has shown that in many cases, the type of randomization that was used was flawed. It is only a matter of time before medical journals and regulatory agencies come to realize that we can no longer rely on (or publish) flawed trials, and that flawed randomization in and of itself disqualifies a trial from being robust or high quality, even if that trial is of high quality otherwise. This book will help to clarify the role randomization plays in ensuring internal validity, and in drawing valid inferences from the data. The various chapters cover a variety of randomization methods, and are not limited to the most common (and most flawed) ones. Readers will come away with a profound understanding of what constitutes a valid randomization procedure, so that they can distinguish the valid from the flawed among not only existing methods but also methods yet to be developed.