For surveys involving sensitive questions, randomized response techniques (RRTs) and other indirect questions are helpful in obtaining survey responses while maintaining the privacy of the respondents. Written by one of the leading experts in the world on RR, Randomized Response and Indirect Questioning Techniques in Surveys describes the current state of RR as well as emerging developments in the field. The author also explains how to extend RR to situations employing unequal probability sampling. While the theory of RR has grown phenomenally, the area has not kept pace in practice. Covering both theory and practice, the book first discusses replacing a direct response (DR) with an RR in a simple random sample with replacement (SRSWR). It then emphasizes how the application of RRTs in the estimation of attribute or quantitative features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers optional RR devices, which provide alternatives to compulsory randomized response theory; and presents RR techniques that encompass quantitative variables, including those related to stigmatizing characteristics. He also gives his viewpoint on alternative RR techniques, including the item count technique, nominative technique, and three-card method.

Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits tackles how to gather and analyze data relating to stigmatizing human traits. S.L. Warner invented RRT and published it in JASA, 1965. In the 50 years since, the subject has grown tremendously, with continued growth. This book comprehensively consolidates the literature to commemorate the inception of RR.

This venture aspires to be a mix of a textbook at the undergraduate and postgraduate levels and a monograph to catch the attention of researchers in theoretical and practical aspects of survey sampling at diverse levels demanding a comprehensive review of what useful materials have preceded, with an eye to what beacons to the depth of the imminent future.

For surveys involving sensitive questions, randomized response techniques (RRTs) and other indirect questions are helpful in obtaining survey responses while maintaining the privacy of the respondents. Written by one of the leading experts in the world on RR, Randomized Response and Indirect Questioning Techniques in Surveys describes the current state of RR as well as emerging developments in the field. The author also explains how to extend RR to situations employing unequal probability sampling. While the theory of RR has grown phenomenally, the area has not kept pace in practice. Covering both theory and practice, the book first discusses replacing a direct response (DR) with an RR in a simple random sample with replacement (SRSWR). It then emphasizes how the application of RRTs in the estimation of attribute or quantitative features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers optional RR devices, which provide alternatives to compulsory randomized response theory; and presents RR techniques that encompass quantitative variables, including those related to stigmatizing characteristics. He also gives his viewpoint on alternative RR techniques, including the item count technique, nominative technique, and three-card method.

Since publication of the first edition in 1992, the field of survey sampling has grown considerably. This new edition of Survey Sampling: Theory and Methods has been updated to include the latest research and the newest methods. The authors have undertaken the daunting task of surveying the sampling literature of the past decade to provide an outstanding research reference. Starting with the unified theory, the authors explain in the clearest of terms the subsequent developments. In fact, even the most modern innovations of survey sampling, both methodological and theoretical, have found a place in this concise volume. See what's new in the Second Edition: -Descriptions of new developments -A wider range of approaches to common problems -Increased coverage of methods that combine design and model-based approaches, adjusting for sample errors Covering the current state of development of essential aspects of theory and methods of survey sampling, the authors have taken great care to avoid being dogmatic and eschew taking sides in their presentation. They have created tool for graduate and advanced level students and a reference for researchers and practitioners that goes beyond the coverage found in most textbooks.

Since publication of the first edition in 1992, the field of survey sampling has grown considerably. This new edition of Survey Sampling: Theory and Methods has been updated to include the latest research and the newest methods. The authors have undertaken the daunting task of surveying the sampling literature of the past decade to provide an outstanding research reference. Starting with the unified theory, the authors explain in the clearest of terms the subsequent developments. In fact, even the most modern innovations of survey sampling, both methodological and theoretical, have found a place in this concise volume. See what's new in the Second Edition: Descriptions of new developments A wider range of approaches to common problems Increased coverage of methods that combine design and model-based approaches, adjusting for sample errors Covering the current state of development of essential aspects of theory and methods of survey sampling, the authors have taken great care to avoid being dogmatic and eschew taking sides in their presentation. They have created tool for graduate and advanced level students and a reference for researchers and practitioners that goes beyond the coverage found in most textbooks.

Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems, hitting upon possible solutions. The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample's behavior and assess the elements of discrepancies. Including case studies, exercises, and solutions, the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling, before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.

As a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation. The book focuses on a wide range of topics which included Bayesian and Empirical Bayesian approaches, complex procedures of stratification, clustering, sampling in multi stages and phases, linear and non-linear estimation of parameters, small area estimation by spatial and chronological modelling, network and adaptive sampling methods and more. The book includes detailed case studies and exercises, making it valuable for students of statistics, specifically survey sampling. 

As a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation. The book focuses on a wide range of topics which included Bayesian and Empirical Bayesian approaches, complex procedures of stratification, clustering, sampling in multi stages and phases, linear and non-linear estimation of parameters, small area estimation by spatial and chronological modelling, network and adaptive sampling methods and more. The book includes detailed case studies and exercises, making it valuable for students of statistics, specifically survey sampling.

This book includes speeches given during five seminar sessions held in honor of Prof. C. R. Rao, on his 100th year. This book also contains a few write-ups touching on the diverse aspects of this august personality. The chapters pay tribute to Prof. C. R. Rao, the Padma Vibhushan awardee, by discussing his life and contributions to the field of statistics. The book also includes a chapter by the Abel Prize winner Prof. S. R. Varadhan who happened to successfully complete his Ph.D. under the guidance of Prof. C. R. Rao.

Combining the two statistical techniques of network sampling and adaptive sampling, this book illustrates the advantages of using them in tandem to effectively capture sparsely located elements in unknown pockets. It shows how network sampling is a reliable guide in capturing inaccessible entities through linked auxiliaries. The text also explores how adaptive sampling is strengthened in information content through subsidiary sampling with devices to mitigate unmanageable expanding sample sizes. Empirical data illustrates the applicability of both methods.

Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems, hitting upon possible solutions. The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample's behavior and assess the elements of discrepancies. Including case studies, exercises, and solutions, the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling, before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.