Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deploy design features in order to control both nonresponse and measurement errors. ASD aims at the optimal matching of design features and the characteristics of respondents given the survey budget. Such a goal is sensible, but ASD requires investment in more advanced technical systems and management infrastructure and asks for the collection of relevant auxiliary data. So what are current best practices in ASD? And is ASD worthwhile when the same auxiliary data are employed in the estimation afterwards? In this book, the authors provide answers to these questions, and much more.

Application and Role of Statistics in Multi-Disciplinary Research Advancement in research requires multi-disciplinary orientation for providing sustainable solutions to political, economic, social, psychological or international problems and statistics has emerged as a separate discipline for enriching other disciplines of study. The purpose of bringing this book is to disseminate the dissections and cross dissections of multi-disciplinary philosophy and mission of the Central University of Haryana. The present edited book is a compilation of selected research papers which were presented during a Two Days National Seminar on Application and Role of Statistics in Multi-Disciplinary Research organised in the Central University of Haryana on 23rd-24th Oct. 2013. This volume comprises mainly five sections. Section-1 comprises of papers in the areas of 'Application of Statistics in Embryonic Economic Issues' dealing with issues of crop diversification, stock market volatility due to macro-economic factors and the food products industry. Section-2 includes research articles in 'Role and Application of Statistics in Business Decision Areas' which focus on the issues related to financial inclusion, Islamic finance, risk in e-transaction and retention policy. Section-3 covers the articles in the areas of “Emerging Dimensions of Statistics in Various Sectors” covering the use of statistics in medical science, engineering and designing. Sections-4 is composed of the papers from the areas of 'Statistics in Social Science, Policy Planning and Governance” where papers emphasising on skill inclusion in degree curricula, co-operative banking and statistical challenges in law and politics are included. The last Section-5 covers the research articles from the areas of 'Statistics in Management of Financial Services in which empirical articles on service quality in banks and health insurance aspects are added from perceptual viewpoints. Though the papers have been selected from different disciplines of study, an attempt is made to reflect the cross-disciplinary ideological churning testified by statistical analysis-empirical as well as conceptual. Overall this edited volume is assimilation, dissection and cross dissection of various disciplines using statistical tools and techniques. Hope this edited version will serve the purpose of scholars, researchers and teachers to navigate into a deep sea of multi-disciplinary insights.

Contributed in honour of Lucien Le Cam on the occasion of his 70th birthday, the papers reflect the immense influence that his work has had on modern statistics. They include discussions of his seminal ideas, historical perspectives, and contributions to current research - spanning two centuries with a new translation of a paper of Daniel Bernoulli. The volume begins with a paper by Aalen, which describes Le Cams role in the founding of the martingale analysis of point processes, and ends with one by Yu, exploring the position of just one of Le Cams ideas in modern semiparametric theory. The other 27 papers touch on areas such as local asymptotic normality, contiguity, efficiency, admissibility, minimaxity, empirical process theory, and biological medical, and meteorological applications - where Le Cams insights have laid the foundations for new theories.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

In clinical medicine appropriate statistics has become indispensable to evaluate treatment effects. Randomized controlled trials are currently the only trials that truly provide evidence-based medicine. Evidence based medicine has become crucial to optimal treatment of patients. We can define randomized controlled trials by using Christopher J. Bulpitt’s definition “a carefully and ethically designed experiment which includes the provision of adequate and appropriate controls by a process of randomization, so that precisely framed questions can be answered”. The answers given by randomized controlled trials constitute at present the way how patients should be clinically managed. In the setup of such randomized trial one of the most important issues is the statistical basis. The randomized trial will never work when the statistical grounds and analyses have not been clearly defined beforehand. All endpoints should be clearly defined in order to perform appropriate power calculations. Based on these power calculations the exact number of available patients can be calculated in order to have a sufficient quantity of individuals to have the predefined questions answered. Therefore, every clinical physician should be capable to understand the statistical basis of well performed clinical trials. It is therefore a great pleasure that Drs. T. J. Cleophas, A. H. Zwinderman, and T. F. Cleophas have published a book on statistical analysis of clinical trials. The book entitled “Statistics Applied to Clinical Trials” is clearly written and makes complex issues in statistical analysis transparant.

This text explains to consumers of research how to read, understand, and critically evaluate the statistical information contained in technical research reports. Excerpts from over 500 recent research articles are presented and discussed to illustrate concepts.