Bayesian Multilevel Models For Repeated Measures Data
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Bayesian Multilevel Models For Repeated Measures Data
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Author : Santiago Barreda
language : en
Publisher: Taylor & Francis
Release Date : 2023-05-18
Bayesian Multilevel Models For Repeated Measures Data written by Santiago Barreda and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-18 with Psychology categories.
This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language. Featuring a series of fully worked analyses of repeated measures data, the focus is placed on active learning through the analyses of the progressively more complicated models presented throughout the book. In this book, the authors offer an introduction to statistics entirely focused on repeated measures data beginning with very simple two-group comparisons and ending with multinomial regression models with many ‘random effects’. Across 13 well-structured chapters, readers are provided with all the code necessary to run all the analyses and make all the plots in the book, as well as useful examples of how to interpret and write up their own analyses. This book provides an accessible introduction for readers in any field, with any level of statistical background. Senior undergraduate students, graduate students, and experienced researchers looking to ‘translate’ their skills with more traditional models to a Bayesian framework will benefit greatly from the lessons in this text.
Bayesian Hierarchical Models
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Author : Peter D. Congdon
language : en
Publisher: CRC Press
Release Date : 2019-09-16
Bayesian Hierarchical Models written by Peter D. Congdon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-16 with Mathematics categories.
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
Applied Survey Data Analysis
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Author : Steven G. Heeringa
language : en
Publisher: CRC Press
Release Date : 2010-04-05
Applied Survey Data Analysis written by Steven G. Heeringa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-05 with Mathematics categories.
Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data. It emphasizes methods and worked examples using available software procedures while reinforcing the principles and theory that underlie those methods. After introducing a step-by-step process for approaching a survey analysis problem, the book presents the fundamental features of complex sample designs and shows how to integrate design characteristics into the statistical methods and software for survey estimation and inference. The authors then focus on the methods and models used in analyzing continuous, categorical, and count-dependent variables; event history; and missing data problems. Some of the techniques discussed include univariate descriptive and simple bivariate analyses, the linear regression model, generalized linear regression modeling methods, the Cox proportional hazards model, discrete time models, and the multiple imputation analysis method. The final chapter covers new developments in survey applications of advanced statistical techniques, including model-based analysis approaches. Designed for readers working in a wide array of disciplines who use survey data in their work, this book also provides a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. A guide to the applied statistical analysis and interpretation of survey data, it contains many examples and practical exercises based on major real-world survey data sets. Although the authors use Stata for most examples in the text, they offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s website: http://www.isr.umich.edu/src/smp/asda/
Human Growth And Development
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Author : Noel Cameron
language : en
Publisher: Academic Press
Release Date : 2021-11-18
Human Growth And Development written by Noel Cameron and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-18 with Science categories.
Human Growth and Development, Third Edition provides a comprehensive volume covering the biology of human growth and the genetic, endocrine, environmental, nutritional, and socio-economic factors that contribute towards its full expression. Human Growth and Development continues to be a valuable resource for researchers, professors and graduate students across the interdisciplinary area of human development. For the new edition, updates are made to all fourteen of the "core chapters" of the book which form the essential reading for a comprehensive understanding of human growth and development. Additionally, new special topics are covered including the interpretation of recently found sub-adult fossils that expand our understanding of the evolution of human growth and a discussion of the early pattern of growth and development as the developmental origins of risk for non-communicable diseases of adulthood. Human Growth and Development, Third Edition includes contributions from the well-known experts in the field and is the most reputable, comprehensive resource available. - New chapters include the impact of physical activity across childhood and adolescence, information on the evolution of the human growth pattern and the contribution of epigenetics to our understanding of human growth - Offers the necessary tools to connect human development data with predictive medicine - Provides extensive depth on content in the form of easily digestible lecture length chapters
Multilevel Statistical Models
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Author : Harvey Goldstein
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-08
Multilevel Statistical Models written by Harvey Goldstein 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 2011-07-08 with Mathematics categories.
Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages. A thorough understanding of these techniques is therefore important for all those working in these areas. This new edition of Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived. Bayesian methodology using MCMC has been extended along with new material on smoothing models, multivariate responses, missing data, latent normal transformations for discrete responses, structural equation modeling and survival models. Key Features: Provides a clear introduction and a comprehensive account of multilevel models. New methodological developments and applications are explored. Written by a leading expert in the field of multilevel methodology. Illustrated throughout with real-life examples, explaining theoretical concepts. This book is suitable as a comprehensive text for postgraduate courses, as well as a general reference guide. Applied statisticians in the social sciences, economics, biological and medical disciplines will find this book beneficial.
Handbook Of Advanced Multilevel Analysis
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Author : Joop Hox
language : en
Publisher: Routledge
Release Date : 2011-01-11
Handbook Of Advanced Multilevel Analysis written by Joop Hox and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-11 with Psychology categories.
This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.
Confirmatory Factor Analysis For Applied Research Second Edition
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Author : Timothy A. Brown
language : en
Publisher: Guilford Publications
Release Date : 2015-01-08
Confirmatory Factor Analysis For Applied Research Second Edition written by Timothy A. Brown and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-08 with Psychology categories.
This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...
Multilevel Synthesis
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Author : Daniel Courgeau
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-03
Multilevel Synthesis written by Daniel Courgeau 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 2007-05-03 with Social Science categories.
This book aims to show how the multilevel approach successfully overcomes the divisions that emerged during the rise of the social sciences— specifically, here, demography and statistics—from the seventeenth century to the present. We begin by examining how the approach connects different branches of the social sciences that conducted their observation and analysis at different levels or addressed different aspects of human complexity. Next, we describe in greater detail the statistical methods and techniques that it can use to simultaneously identify and measure the effects of the different levels examined on the characteristics studied. To introduce this work, we first provide an overview of the goal of social sciences, before discussing the various levels of aggregation at which they can operate. Social sciences start from the observation of a real-life experience and then seek to structure it according to different fields, which constitute the specific objects of study for each science. As a rule, these objects are defined independently of the scale and levels of aggregation that can be chosen to observe them. For example, the object of demography is the quantitative study of human populations, their variations, and their status, without specifying whether the level chosen is the individual, the family, the population of a town, or that of a country. Likewise, economics studies the production, distribution, and consumption of wealth, without specifying if the analysis is of an individual, a market, a firm or a nation.
The Sage Handbook Of Multilevel Modeling
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Author : Marc A. Scott
language : en
Publisher: SAGE
Release Date : 2013-08-31
The Sage Handbook Of Multilevel Modeling written by Marc A. Scott and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-31 with Reference categories.
In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.
Statistical Intervals
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Author : William Q. Meeker
language : en
Publisher: John Wiley & Sons
Release Date : 2017-08-22
Statistical Intervals written by William Q. Meeker 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 2017-08-22 with Mathematics categories.
Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.