Current Trends In Bayesian Methodology With Applications

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Current Trends in Bayesian Methodology with Applications

Author : Satyanshu K. Upadhyay
Publisher : CRC Press
ISBN 13 : 1482235129
Total Pages : 674 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Current Trends in Bayesian Methodology with Applications by : Satyanshu K. Upadhyay

Download or read book Current Trends in Bayesian Methodology with Applications written by Satyanshu K. Upadhyay and published by CRC Press. This book was released on 2015-05-21 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples. This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.

Bayesian Statistics, New Generations New Approaches

Author : Alejandra Avalos-Pacheco
Publisher : Springer Nature
ISBN 13 : 3031424131
Total Pages : 119 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Bayesian Statistics, New Generations New Approaches by : Alejandra Avalos-Pacheco

Download or read book Bayesian Statistics, New Generations New Approaches written by Alejandra Avalos-Pacheco and published by Springer Nature. This book was released on 2024-01-06 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22–23, titled "Bayesian Statistics, New Generations New Approaches". This collection features selected peer-reviewed contributions that showcase the vibrant and diverse research presented at meeting. This book is intended for a broad audience interested in statistics and aims at providing stimulating contributions to theoretical, methodological, and computational aspects of Bayesian statistics. The contributions highlight various topics in Bayesian statistics, presenting promising methodological approaches to address critical challenges across diverse applications. This compilation stands as a testament to the talent and potential within the j-ISBA community. This book is meant to serve as a catalyst for continued advancements in Bayesian methodology and its applications and encourages fruitful collaborations that push the boundaries of statistical research.

Bayesian Inference in the Social Sciences

Author : Ivan Jeliazkov
Publisher : John Wiley & Sons
ISBN 13 : 1118771125
Total Pages : 266 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Bayesian Inference in the Social Sciences by : Ivan Jeliazkov

Download or read book Bayesian Inference in the Social Sciences written by Ivan Jeliazkov and published by John Wiley & Sons. This book was released on 2014-11-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance Emphasizing interdisciplinary coverage, Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus. Bayesian Inference in the Social Sciences features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include: Real-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance State-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website Interdisciplinary coverage from well-known international scholars and practitioners Bayesian Inference in the Social Sciences is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.

Bayesian Phylogenetics

Author : Ming-Hui Chen
Publisher : CRC Press
ISBN 13 : 1466500794
Total Pages : 398 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Bayesian Phylogenetics by : Ming-Hui Chen

Download or read book Bayesian Phylogenetics written by Ming-Hui Chen and published by CRC Press. This book was released on 2014-05-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.

Bayesian Inference - Recent Trends

Author : İhsan Bucak
Publisher : BoD – Books on Demand
ISBN 13 : 1837693560
Total Pages : 90 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Bayesian Inference - Recent Trends by : İhsan Bucak

Download or read book Bayesian Inference - Recent Trends written by İhsan Bucak and published by BoD – Books on Demand. This book was released on 2024-01-17 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an era where data is abundant and computational power is soaring, Bayesian Inference - Recent Trends emerges as an essential guide to understanding and applying Bayesian methods in various scientific and technological domains. This book uniquely blends theoretical rigor with practical insights, showcasing the latest advancements and applications of Bayesian inference. • Discover the renaissance of Bayesian inference and its vital role in modern-day statistical analysis and prediction. • Explore the depth of hidden Markov models and their power in inferring hidden states and transitions in stochastic systems. • Dive into the complexity of nested sampling and its effectiveness in parameter estimation, particularly in signal processing. • Examine the precision of naive Bayes algorithms in news classification, a critical task in the digital information age. This book is an invaluable resource for anyone interested in the intersection of statistics, machine learning, and data science. It offers a unique perspective on Bayesian inference, revealing its potential to provide robust solutions in an increasingly data-driven world. Whether you are a seasoned researcher, a budding scientist, or a curious enthusiast, Bayesian Inference - Recent Trends is your gateway to understanding and leveraging the power of Bayesian methods in the ever-evolving landscape of data analysis.

Bayesian Hierarchical Models

Author : Peter D. Congdon
Publisher : CRC Press
ISBN 13 : 0429532903
Total Pages : 506 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Bayesian Hierarchical Models by : Peter D. Congdon

Download or read book Bayesian Hierarchical Models written by Peter D. Congdon and published by CRC Press. This book was released on 2019-09-16 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website

Frontiers of Statistical Decision Making and Bayesian Analysis

Author : Ming-Hui Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1441969446
Total Pages : 631 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen

Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer Science & Business Media. This book was released on 2010-07-24 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.

Bayesian Statistics 9

Author : José M. Bernardo
Publisher : Oxford University Press
ISBN 13 : 0191627852
Total Pages : pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis Bayesian Statistics 9 by : José M. Bernardo

Download or read book Bayesian Statistics 9 written by José M. Bernardo and published by Oxford University Press. This book was released on 2011-10-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Valencia International Meetings on Bayesian Statistics - established in 1979 and held every four years - have been the forum for a definitive overview of current concerns and activities in Bayesian statistics. These are the edited Proceedings of the Ninth meeting, and contain the invited papers each followed by their discussion and a rejoinder by the authors(s). In the tradition of the earlier editions, this encompasses an enormous range of theoretical and applied research, high lighting the breadth, vitality and impact of Bayesian thinking in interdisciplinary research across many fields as well as the corresponding growth and vitality of core theory and methodology. The Valencia 9 invited papers cover a broad range of topics, including foundational and core theoretical issues in statistics, the continued development of new and refined computational methods for complex Bayesian modelling, substantive applications of flexible Bayesian modelling, and new developments in the theory and methodology of graphical modelling. They also describe advances in methodology for specific applied fields, including financial econometrics and portfolio decision making, public policy applications for drug surveillance, studies in the physical and environmental sciences, astronomy and astrophysics, climate change studies, molecular biosciences, statistical genetics or stochastic dynamic networks in systems biology.

Bayesian Astrophysics

Author : Andrés Asensio Ramos
Publisher : Cambridge University Press
ISBN 13 : 1107102138
Total Pages : 209 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Bayesian Astrophysics by : Andrés Asensio Ramos

Download or read book Bayesian Astrophysics written by Andrés Asensio Ramos and published by Cambridge University Press. This book was released on 2018-04-26 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of the fundamentals of Bayesian inference and its applications within astrophysics, for graduate students and researchers.

Bayesian Theory and Methods with Applications

Author : Vladimir Savchuk
Publisher : Springer Science & Business Media
ISBN 13 : 9491216147
Total Pages : 327 pages
Book Rating : 4.4/5 (912 download)

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Book Synopsis Bayesian Theory and Methods with Applications by : Vladimir Savchuk

Download or read book Bayesian Theory and Methods with Applications written by Vladimir Savchuk and published by Springer Science & Business Media. This book was released on 2011-09-01 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods are growing more and more popular, finding new practical applications in the fields of health sciences, engineering, environmental sciences, business and economics and social sciences, among others. This book explores the use of Bayesian analysis in the statistical estimation of the unknown phenomenon of interest. The contents demonstrate that where such methods are applicable, they offer the best possible estimate of the unknown. Beyond presenting Bayesian theory and methods of analysis, the text is illustrated with a variety of applications to real world problems.

Computational Statistical Methodologies and Modeling for Artificial Intelligence

Author : Priyanka Harjule
Publisher : CRC Press
ISBN 13 : 1000831094
Total Pages : 359 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Computational Statistical Methodologies and Modeling for Artificial Intelligence by : Priyanka Harjule

Download or read book Computational Statistical Methodologies and Modeling for Artificial Intelligence written by Priyanka Harjule and published by CRC Press. This book was released on 2023-03-31 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Bayesian Theory and Applications

Author : Paul Damien
Publisher : OUP Oxford
ISBN 13 : 0191647004
Total Pages : 717 pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis Bayesian Theory and Applications by : Paul Damien

Download or read book Bayesian Theory and Applications written by Paul Damien and published by OUP Oxford. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics.

Small Area Estimation and Microsimulation Modeling

Author : Azizur Rahman
Publisher : CRC Press
ISBN 13 : 1482260735
Total Pages : 522 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Small Area Estimation and Microsimulation Modeling by : Azizur Rahman

Download or read book Small Area Estimation and Microsimulation Modeling written by Azizur Rahman and published by CRC Press. This book was released on 2016-11-30 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.

Bayesian Thinking, Modeling and Computation

Author :
Publisher : Elsevier
ISBN 13 : 0080461174
Total Pages : 1062 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Bayesian Thinking, Modeling and Computation by :

Download or read book Bayesian Thinking, Modeling and Computation written by and published by Elsevier. This book was released on 2005-11-29 with total page 1062 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians. Critical thinking on causal effects Objective Bayesian philosophy Nonparametric Bayesian methodology Simulation based computing techniques Bioinformatics and Biostatistics

Data Driven Methods for Civil Structural Health Monitoring and Resilience

Author : Mohammad Noori
Publisher : CRC Press
ISBN 13 : 1000965589
Total Pages : 459 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Data Driven Methods for Civil Structural Health Monitoring and Resilience by : Mohammad Noori

Download or read book Data Driven Methods for Civil Structural Health Monitoring and Resilience written by Mohammad Noori and published by CRC Press. This book was released on 2023-10-26 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.

Methods for Single-Cell and Microbiome Sequencing Data

Author : Himel Mallick
Publisher : Frontiers Media SA
ISBN 13 : 2889762807
Total Pages : 129 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Methods for Single-Cell and Microbiome Sequencing Data by : Himel Mallick

Download or read book Methods for Single-Cell and Microbiome Sequencing Data written by Himel Mallick and published by Frontiers Media SA. This book was released on 2022-05-31 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Small Sample Size Solutions

Author : Rens van de Schoot
Publisher : Routledge
ISBN 13 : 1000760944
Total Pages : 270 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Small Sample Size Solutions by : Rens van de Schoot

Download or read book Small Sample Size Solutions written by Rens van de Schoot and published by Routledge. This book was released on 2020-02-13 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers often have difficulties collecting enough data to test their hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the research question. This unique book provides guidelines and tools for implementing solutions to issues that arise in small sample research. Each chapter illustrates statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small. This essential book will enable social and behavioral science researchers to test their hypotheses even when the statistical model required for answering their research question is too complex for the sample sizes they can collect. The statistical models in the book range from the estimation of a population mean to models with latent variables and nested observations, and solutions include both classical and Bayesian methods. All proposed solutions are described in steps researchers can implement with their own data and are accompanied with annotated syntax in R. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology to psychology, marketing, and economics.