Following the chronological development of sample surveys, this book provides an analysis of the mathematical and statistical theory of the subject. The text begins with the mathematics of randomized sampling designs as well as a general treatment of estimation of population totals through the Horvits-Thompson estimator and its variants. The book then examines approximations and limit theorems for the distribution of the estimators and design-based estimation of other population quantities. It concludes with chapters concerning inference from surveys. Theory of Sample Surveys will assist in a range of applications, including: auditing quality monitoring market research wildlife surveys mining exploration agriculture and business surveys population health studies This book acts as an exceptional resource for survey methodologists in government organizations as well as lecturers and graduate students in statistics and biostatistics.
This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.
Author: Ettore Lanzarone
Publisher: Springer Science & Business Media
Release Date: 2013-11-22
The first Bayesian Young Statisticians Meeting, BAYSM 2013, has provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and post-docs dealing with Bayesian statistics to connect with the Bayesian community at large, exchange ideas, and network with scholars working in their field. The Workshop, which took place June 5th and 6th 2013 at CNR-IMATI, Milan, has promoted further research in all the fields where Bayesian statistics may be employed under the guidance of renowned plenary lecturers and senior discussants. A selection of the contributions to the meeting and the summary of one of the plenary lectures compose this volume.
This four-volume reference work builds upon the success of past editions of Elsevier’s Corrosion title (by Shreir, Jarman, and Burstein), covering the range of innovations and applications that have emerged in the years since its publication. Developed in partnership with experts from the Corrosion and Protection Centre at the University of Manchester, Shreir’s Corrosion meets the research and productivity needs of engineers, consultants, and researchers alike. Incorporates coverage of all aspects of the corrosion phenomenon, from the science behind corrosion of metallic and non-metallic materials in liquids and gases to the management of corrosion in specific industries and applications Features cutting-edge topics such as medical applications, metal matrix composites, and corrosion modeling Covers the benefits and limitations of techniques from scanning probes to electrochemical noise and impedance spectroscopy
Author: Timothy P. Johnson
Publisher: John Wiley & Sons
Release Date: 2014-10-13
A comprehensive guidebook to the current methodologies and practices used in health surveys A unique and self-contained resource, Handbook of Health Survey Methods presents techniques necessary for confronting challenges that are specific to health survey research. The handbook guides readers through the development of sample designs, data collection procedures, and analytic methods for studies aimed at gathering health information on general and targeted populations. The book is organized into five well-defined sections: Design and Sampling Issues, Measurement Issues, Field Issues, Health Surveys of Special Populations, and Data Management and Analysis. Maintaining an easy-to-follow format, each chapter begins with an introduction, followed by an overview of the main concepts, theories, and applications associated with each topic. Finally, each chapter provides connections to relevant online resources for additional study and reference. The Handbook of Health Survey Methods features: 29 methodological chapters written by highly qualified experts in academia, research, and industry A treatment of the best statistical practices and specific methodologies for collecting data from special populations such as sexual minorities, persons with disabilities, patients, and practitioners Discussions on issues specific to health research including developing physical health and mental health measures, collecting information on sensitive topics, sampling for clinical trials, collecting biospecimens, working with proxy respondents, and linking health data to administrative and other external data sources Numerous real-world examples from the latest research in the fields of public health, biomedicine, and health psychology Handbook of Health Survey Methods is an ideal reference for academics, researchers, and practitioners who apply survey methods and analyze data in the fields of biomedicine, public health, epidemiology, and biostatistics. The handbook is also a useful supplement for upper-undergraduate and graduate-level courses on survey methodology.
Author: Raymond L. Chambers
Publisher: CRC Press
Release Date: 2012-05-02
Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to biased and inefficient estimates. Maximum Likelihood Estimation for Sample Surveys presents an overview of likelihood methods for the analysis of sample survey data that account for the selection methods used, and includes all necessary background material on likelihood inference. It covers a range of data types, including multilevel data, and is illustrated by many worked examples using tractable and widely used models. It also discusses more advanced topics, such as combining data, non-response, and informative sampling. The book presents and develops a likelihood approach for fitting models to sample survey data. It explores and explains how the approach works in tractable though widely used models for which we can make considerable analytic progress. For less tractable models numerical methods are ultimately needed to compute the score and information functions and to compute the maximum likelihood estimates of the model parameters. For these models, the book shows what has to be done conceptually to develop analyses to the point that numerical methods can be applied. Designed for statisticians who are interested in the general theory of statistics, Maximum Likelihood Estimation for Sample Surveys is also aimed at statisticians focused on fitting models to sample survey data, as well as researchers who study relationships among variables and whose sources of data include surveys.
Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression.
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.
Assuming a basic knowledge of the frequentist approach to finite population sampling, Bayesian Methods for Finite Population Sampling describes Bayesian and predictive approaches to inferential problems with an emphasis on the likelihood principle. The authors demonstrate that a variety of levels of prior information can be used in survey sampling in a Bayesian manner. Situations considered range from a noninformative Bayesian justification of standard frequentist methods when the only prior information available is the belief in the exchangeability of the units to a full-fledged Bayesian model. Intended primarily for graduate students and researchers in finite population sampling, this book will also be of interest to statisticians who use sampling and lecturers and researchers in general statistics and biostatistics.
Setting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistical issues to clients, draw attention to common methodological errors, and provide references to essential literature. The first full text on design-based stereology opens with a review of classical and modern stereology, followed by a treatment of mathematical foundations and then on to core techniques. The final chapters discuss implementing techniques in practical sampling designs, summarize understanding of the variance of stereological estimators, and describe open problems for further research. The book also details isotropic, vertical or local sampling designs for estimating stereological parameters such as volume, surface area, particle number and spatial distribution. This extensive text offers support to statistical consultants using examples, applications and unique Advice to Consultants sections. It contains numerous literature references, bibliographic notes and nearly 150 illustrations.
Author: Tamás Rudas
Publisher: SAGE Publications
Release Date: 2008-02-21
Genre: Social Science
"This is a valuable reference guide for readers interested in gaining a basic understanding of probability theory or its applications in problem solving in the other disciplines." —CHOICE Providing cutting-edge perspectives and real-world insights into the greater utility of probability and its applications, the Handbook of Probability offers an equal balance of theory and direct applications in a non-technical, yet comprehensive, format. Editor Tamás Rudas and the internationally-known contributors present the material in a manner so that researchers of various backgrounds can use the reference either as a primer for understanding basic probability theory or as a more advanced research tool for specific projects requiring a deeper understanding. The wide-ranging applications of probability presented make it useful for scholars who need to make interdisciplinary connections in their work. Key Features Contains contributions from the international who's-who of probability across several disciplines Offers an equal balance of theory and applications Explains the most important concepts of probability theory in a non-technical yet comprehensive way Provides in-depth examples of recent applications in the social and behavioral sciences as well as education, business, and law Intended Audience This Handbook makes an ideal library purchase. In addition, this volume should also be of interest to individual scholars in the social and behavioral sciences.