Capture Recapture Methods For The Social And Medical Sciences
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Capture Recapture Methods For The Social And Medical Sciences
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Author : Dankmar Bohning
language : en
Publisher: CRC Press
Release Date : 2017-07-28
Capture Recapture Methods For The Social And Medical Sciences written by Dankmar Bohning and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Mathematics categories.
Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas.
Introduction To Probability Statistics R
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Author : Sujit K. Sahu
language : en
Publisher: Springer Nature
Release Date : 2024-04-01
Introduction To Probability Statistics R written by Sujit K. Sahu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-01 with Mathematics categories.
A strong grasp of elementary statistics and probability, along with basic skills in using R, is essential for various scientific disciplines reliant on data analysis. This book serves as a gateway to learning statistical methods from scratch, assuming a solid background in high school mathematics. Readers gradually progress from basic concepts to advanced statistical modelling, with examples from actuarial, biological, ecological, engineering, environmental, medicine, and social sciences highlighting the real-world relevance of the subject. An accompanying R package enables seamless practice and immediate application, making it ideal for beginners. The book comprises 19 chapters divided into five parts. Part I introduces basic statistics and the R software package, teaching readers to calculate simple statistics and create basic data graphs. Part II delves into probability concepts, including rules and conditional probability, and introduces widelyused discrete and continuous probability distributions (e.g., binomial, Poisson, normal, log-normal). It concludes with the central limit theorem and joint distributions for multiple random variables. Part III explores statistical inference, covering point and interval estimation, hypothesis testing, and Bayesian inference. This part is intentionally less technical, making it accessible to readers without an extensive mathematical background. Part IV addresses advanced probability and statistical distribution theory, assuming some familiarity with (or concurrent study of) mathematical methods like advanced calculus and linear algebra. Finally, Part V focuses on advanced statistical modelling using simple and multiple regression and analysis of variance, laying the foundation for further studies in machine learning and data science applicable to various data and decision analytics contexts. Based on years of teaching experience, this textbook includes numerousexercises and makes extensive use of R, making it ideal for year-long data science modules and courses. In addition to university courses, the book amply covers the syllabus for the Actuarial Statistics 1 examination of the Institute and Faculty of Actuaries in London. It also provides a solid foundation for postgraduate studies in statistics and probability, or a reliable reference for statistics.
Analysis Of Integrated Data
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Author : Li-Chun Zhang
language : en
Publisher: CRC Press
Release Date : 2019-04-18
Analysis Of Integrated Data written by Li-Chun Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-18 with Mathematics categories.
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Administrative Records For Survey Methodology
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Author : Asaph Young Chun
language : en
Publisher: John Wiley & Sons
Release Date : 2021-02-25
Administrative Records For Survey Methodology written by Asaph Young Chun and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-25 with Mathematics categories.
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGY Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology is a comprehensive guide to improving the quality, cost-efficiency, and interpretability of surveys and censuses using administrative data research. Contributions from a team of internationally-recognized experts provide practical approaches for integrating administrative data in statistical surveys, and discuss the methodological issues—including concerns of privacy, confidentiality, and legality—involved in collecting and analyzing administrative records. Numerous real-world examples highlight technological and statistical innovations, helping readers gain a better understanding of both fundamental methods and advanced techniques for controlling data quality reducing total survey error. Divided into four sections, the first describes the basics of administrative records research and addresses disclosure limitation and confidentiality protection in linked data. Section two focuses on data quality and linking methodology, covering topics such as quality evaluation, measuring and controlling for non-consent bias, and cleaning and using administrative lists. The third section examines the use of administrative records in surveys and includes case studies of the Swedish register-based census and the administrative records applications used for the US 2020 Census. The book’s final section discusses combining administrative and survey data to improve income measurement, enhancing health surveys with data linkage, and other uses of administrative data in evidence-based policymaking. This state-of-the-art resource: Discusses important administrative data issues and suggests how administrative data can be integrated with more traditional surveys Describes practical uses of administrative records for evidence-driven decisions in both public and private sectors Emphasizes using interdisciplinary methodology and linking administrative records with other data sources Explores techniques to leverage administrative data to improve the survey frame, reduce nonresponse follow-up, assess coverage error, measure linkage non-consent bias, and perform small area estimation. Administrative Records for Survey Methodology is an indispensable reference and guide for statistical researchers and methodologists in academia, industry, and government, particularly census bureaus and national statistical offices, and an ideal supplemental text for undergraduate and graduate courses in data science, survey methodology, data collection, and data analysis methods.
Model Based Geostatistics For Global Public Health
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Author : Peter J. Diggle
language : en
Publisher: CRC Press
Release Date : 2019-03-04
Model Based Geostatistics For Global Public Health written by Peter J. Diggle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-04 with Technology & Engineering categories.
Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the authors describe and explain the pattern of spatial variation in a health outcome or exposure measurement of interest. Model-based geostatistics uses explicit probability models and established principles of statistical inference to address questions of this kind. Features: Presents state-of-the-art methods in model-based geostatistics. Discusses the application these methods some of the most challenging global public health problems including disease mapping, exposure mapping and environmental epidemiology. Describes exploratory methods for analysing geostatistical data, including: diagnostic checking of residuals standard linear and generalized linear models; variogram analysis; Gaussian process models and geostatistical design issues. Includes a range of more complex geostatistical problems where research is ongoing. All of the results in the book are reproducible using publicly available R code and data-sets, as well as a dedicated R package. This book has been written to be accessible not only to statisticians but also to students and researchers in the public health sciences. The Authors Peter Diggle is Distinguished University Professor of Statistics in the Faculty of Health and Medicine, Lancaster University. He also holds honorary positions at the Johns Hopkins University School of Public Health, Columbia University International Research Institute for Climate and Society, and Yale University School of Public Health. His research involves the development of statistical methods for analyzing spatial and longitudinal data and their applications in the biomedical and health sciences. Dr Emanuele Giorgi is a Lecturer in Biostatistics and member of the CHICAS research group at Lancaster University, where he formerly obtained a PhD in Statistics and Epidemiology in 2015. His research interests involve the development of novel geostatistical methods for disease mapping, with a special focus on malaria and other tropical diseases. In 2018, Dr Giorgi was awarded the Royal Statistical Society Research Prize "for outstanding published contribution at the interface of statistics and epidemiology." He is also the lead developer of PrevMap, an R package where all the methodology found in this book has been implemented.
Modern Statistical Methods For Health Research
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Author : Yichuan Zhao
language : en
Publisher: Springer Nature
Release Date : 2021-10-14
Modern Statistical Methods For Health Research written by Yichuan Zhao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-14 with Medical categories.
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
Systematic Reviews In The Social Sciences
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Author : Mark Petticrew
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-15
Systematic Reviews In The Social Sciences written by Mark Petticrew and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Psychology categories.
Such diverse thinkers as Lao-Tze, Confucius, and U.S. Defense Secretary Donald Rumsfeld have all pointed out that we need to be able to tell the difference between real and assumed knowledge. The systematic review is a scientific tool that can help with this difficult task. It can help, for example, with appraising, summarising, and communicating the results and implications of otherwise unmanageable quantities of data. This book, written by two highly-respected social scientists, provides an overview of systematic literature review methods: Outlining the rationale and methods of systematic reviews; Giving worked examples from social science and other fields; Applying the practice to all social science disciplines; It requires no previous knowledge, but takes the reader through the process stage by stage; Drawing on examples from such diverse fields as psychology, criminology, education, transport, social welfare, public health, and housing and urban policy, among others. Including detailed sections on assessing the quality of both quantitative, and qualitative research; searching for evidence in the social sciences; meta-analytic and other methods of evidence synthesis; publication bias; heterogeneity; and approaches to dissemination.
Recent Advances On Sampling Methods And Educational Statistics
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Author : Hon Keung Tony Ng
language : en
Publisher: Springer Nature
Release Date : 2022-11-25
Recent Advances On Sampling Methods And Educational Statistics written by Hon Keung Tony Ng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-25 with Mathematics categories.
This edited collection commemorates the career of Dr. S. Lynne Stokes by highlighting recent advances in her areas of research interest, emphasizing practical applications and future directions. It serves as a collective effort of leading statistical scientists who work at the cutting edge in statistical sampling. S. Lynne Stokes is Professor of Statistical Science and Director of the Data Science Institute at Southern Methodist University, and Senior Fellow at the National Institute of Statistical Sciences. She has enjoyed a distinguished research career, making fundamental contributions to a variety of fields in statistical sampling. Reflecting on Professor Stokes' main areas of research, this volume is structured into three main parts: I. ranked-set sampling, judgment post-stratified sampling, and capture-recapture methods II. nonsampling errors in statistical sampling III. educational and behavioral statistics. This collection will be of interest to researchers, advanced students, and professionals in the public and private sectors who would like to learn more about latest advancements in statistical sampling, particularly those who work in educational and behavioral statistics.
Analysis Of Capture Recapture Data
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Author : Rachel S. McCrea
language : en
Publisher: CRC Press
Release Date : 2014-08-01
Analysis Of Capture Recapture Data written by Rachel S. McCrea and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-01 with Mathematics categories.
An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the mortality and size of the populations. Capture-rec
Epidemiology Of Drug Abuse
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Author : Zili Sloboda
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-06-02
Epidemiology Of Drug Abuse written by Zili Sloboda and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-02 with Medical categories.
As the drug abuse epidemic evolves, so do the tools needed to understand and treat it. Accordingly, Epidemiology of Drug Abuse takes the long view, cogently outlining what the book calls "the natural history of drug abuse" and redefining its complex phenomena to reflect our present-day knowledge. Twenty-six eminent contributors discuss the state and future of the field, balancing the practical concerns involved in gathering drug abuse data with the ethics of using the information. - Current thinking on pathways and etiology, as well as medical, psychological, and social sequelae of drug abuse - Proven, up-to-date methodologies for assessment - Challenges of gathering data from high-risk and other user populations - Sampling and application issues - Uses, sources, and limitations of treatment data - Analytical papers applying the methodologies to specific and global studies - The role of epidemiology studies in developing prevention strategies With this multifaceted approach to the subject, Epidemiology of Drug Abuse provides researchers and educators with a reference that sheds significant light on infrequently covered areas. In addition, its breadth and accessibility of coverage make it a teaching text suitable to courses in epidemiology, public health, and drug abuse.