Randomize

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.

In October 2019, Abhijit Banerjee, Esther Duflo, and Michael Kremer jointly won the 51st Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel "for their experimental approach to alleviating global poverty." But what is the exact scope of their experimental method, known as randomized control trials (RCTs)? Which sorts of questions are RCTs able to address and which do they fail to answer? The first of its kind, Randomized Control Trials in the Field of Development: A Critical Perspective provides answers to these questions, explaining how RCTs work, what they can achieve, why they sometimes fail, how they can be improved and why other methods are both useful and necessary. Bringing together leading specialists in the field from a range of backgrounds and disciplines (economics, econometrics, mathematics, statistics, political economy, socioeconomics, anthropology, philosophy, global health, epidemiology, and medicine), it presents a full and coherent picture of the main strengths and weaknesses of RCTs in the field of development. Looking beyond the epistemological, political, and ethical differences underlying many of the disagreements surrounding RCTs, it explores the implementation of RCTs on the ground, outside of their ideal theoretical conditions and reveals some unsuspected uses and effects, their disruptive potential, but also their political uses. The contributions uncover the implicit worldview that many RCTs draw on and disseminate, and probe the gap between the method's narrow scope and its success, while also proposing improvements and alternatives. Without disputing the contribution of RCTs to scientific knowledge, Randomized Control Trials in the Field of Development warns against the potential dangers of their excessive use, arguing that the best use for RCTs is not necessarily that which immediately springs to mind. Written in plain language, this book offers experts and laypeople alike a unique opportunity to come to an informed and reasoned judgement on RCTs and what they can bring to development.

Astronomy is the oldest and most fundamental of the natural sciences. From the early beginnings of civilization astronomers have attempted to explain not only what the Universe is and how it works, but also how it started, how it evolved to the present day, and how it will develop in the future. The author, a well-known astronomer himself, describes the evolution of astronomical ideas, briefly discussing most of the instrumental developments. Using numerous figures to elucidate the mechanisms involved, the book starts with the astronomical ideas of the Egyptian and Mesopotamian philosophers, moves on to the Greek period, and then to the golden age of astronomy, i.e. to Copernicus, Galileo, Kepler, and Newton, and ends with modern theories of cosmology. Written with undergraduate students in mind, this book gives a fascinating survey of astronomical thinking.

In cancer research, a traditional phase II trial is designed as a single-arm trial that compares the experimental therapy to a historical control. This simple trial design has led to several adverse issues, including increased false positivity of phase II trial results and negative phase III trials. To rectify these problems, oncologists and biostatisticians have begun to use a randomized phase II trial that compares an experimental therapy with a prospective control therapy. Randomized Phase II Cancer Clinical Trials explains how to properly select and accurately use diverse statistical methods for designing and analyzing phase II trials. The author first reviews the statistical methods for single-arm phase II trials since some methodologies for randomized phase II trials stem from single-arm phase II trials and many phase II cancer clinical trials still use single-arm designs. The book then presents methods for randomized phase II trials and describes statistical methods for both single-arm and randomized phase II trials. Although the text focuses on phase II cancer clinical trials, the statistical methods covered can also be used (with minor modifications) in phase II trials for other diseases and in phase III cancer clinical trials. Suitable for cancer clinicians and biostatisticians, this book shows how randomized phase II trials with a prospective control resolve the shortcomings of traditional single-arm phase II trials. It provides readers with numerous statistical design and analysis methods for randomized phase II trials in oncology.

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

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.

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.

Abstract curricular program implementation in the context of randomized field trials Gloria Isabel Miller This study examined three cases of commercially available curricular program implementations to determine if a unified approach to measuring the level of implementation was possible (proof of concept). Further, the study investigated whether the level of curriculum and implementation plan specificity made a difference to the strength of implementation achieved in classrooms; and described the implementation evolution in different contexts. The study sample consists of a total of 163 teachers in eight school districts across the United States. In each case teachers were randomly assigned to using the curricular innovation or their currently used materials and processes. The three cases, HS-Math, NewScience, and MathIntervention, were purposely chosen to represent three different points of curricular and implementation specificity and two different subject areas, math and science. Each case features a commercially available program that also had opportunities for teachers to use "electronic" technology to enhance their learning or to engage their students. The cases represent differing student grade levels. The cases are different enough to provide a range that exercises the measurement techniques introduced in this study so results can begin to generalize across curricular programs and grades. However, the cases are similar enough in research design, instrumentation, and data collection methods to make them comparable. A key contribution of this investigation is the creation of a framework to measure the level of implementation (the extent to which the teacher and students display the actions, behaviors, and interactions expected by using the innovation). The unified conceptual framework arrived at by using an Activity Theory perspective together with the analytical methods employed provide a way to view the rich complex interaction of implementation as a system with the larger system of the school organization. Data from the analysis revealed that variations in the level of implementation were no different regardless of the level of specificity. A strong finding of this work is that implementation evolves slowly even when the curricular program is scripted and coaching support is provided to teachers. The paper concludes with implications for policy and future research.