Download or read book Applied Regularization Methods for the Social Sciences written by Holmes Finch and published by CRC Press. This book was released on 2022-03-09 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action. Key Features: Description of regularization methods in a user friendly and easy to read manner Inclusion of regularization-based approaches for a variety of statistical analyses commonly used in the social sciences, including both univariate and multivariate models Fully developed extended examples using multiple software packages, including R, SAS, and SPSS Website containing all datasets and software scripts used in the examples Inclusion of both frequentist and Bayesian regularization approaches Application exercises for each chapter that instructors could use in class, and independent researchers could use to practice what they have learned from the book

Download or read book Applied Regularization Methods for the Social Sciences written by Holmes Finch and published by Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences. This book was released on 2022 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action. Key Features: Description of regularization methods in a user friendly and easy to read manner Inclusion of regularization-based approaches for a variety of statistical analyses commonly used in the social sciences, including both univariate and multivariate models Fully developed extended examples using multiple software packages, including R, SAS, and SPSS Website containing all datasets and software scripts used in the examples Inclusion of both frequentist and Bayesian regularization approaches Application exercises for each chapter that instructors could use in class, and independent researchers could use to practice what they have learned from the book

Download or read book Computational Aspects of Psychometric Methods written by Patricia Martinková and published by CRC Press. This book was released on 2023-07-03 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers the main topics of psychometrics such as validity, reliability, item analysis, item response theory models, and computerized adaptive testing. The computational aspects comprise the statistical theory and models, comparison of estimation methods and algorithms, as well as an implementation with practical data examples in R and also in an interactive ShinyItemAnalysis application. Key Features: Statistical models and estimation methods involved in psychometric research Includes reproducible R code and examples with real datasets Interactive implementation in ShinyItemAnalysis application The book is targeted toward a wide range of researchers in the field of educational, psychological, and health-related measurements. It is also intended for those developing measurement instruments and for those collecting and analyzing data from behavioral measurements, who are searching for a deeper understanding of underlying models and further development of their analytical skills.

Download or read book Principles of Psychological Assessment written by Isaac T. Petersen and published by CRC Press. This book was released on 2024-05-02 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the principles of psychological assessment to help researchers and clinicians better develop, evaluate, administer, score, integrate, and interpret psychological assessments. It discusses psychometrics (reliability and validity), the assessment of various psychological domains (behavior, personality, intellectual functioning), various measurement methods (e.g., questionnaires, observations, interviews, biopsychological assessments, performance-based assessments), and emerging analytical frameworks to evaluate and improve assessment including: generalizability theory, structural equation modeling, item response theory, and signal detection theory. The text also discusses ethics, test bias, and cultural and individual diversity. Key Features Gives analysis examples using free software Helps readers apply principles to research and practice Provides text, analysis code/syntax, R output, figures, and interpretations integrated to guide readers Uses the freely available petersenlab package for R Principles of Psychological Assessment: With Applied Examples in R is intended for use by graduate students, faculty, researchers, and practicing psychologists.

Download or read book Regression Analysis in R written by Jocelyn E. Bolin and published by CRC Press. This book was released on 2022-07-27 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples. Key Features: Full output examples complete with interpretation Full syntax examples to help teach R code Appendix explaining basic R functions Methods for multilevel data that are often included in basic regression texts End of Chapter Comprehension Exercises

Download or read book Crime Mapping and Spatial Data Analysis using R written by Juan Medina Ariza and published by CRC Press. This book was released on 2023-04-27 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.

Download or read book Understanding Elections through Statistics written by Ole J. Forsberg and published by CRC Press. This book was released on 2024-10-31 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elections are random events. From individuals deciding whether to vote, to individuals deciding who to vote for, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day... or beyond. Understanding Elections through Statistics explores this random phenomenon from three primary points of view: predicting the election outcome using opinion polls, testing the election outcome using government-reported data, and exploring election data to better understand the people. Written for those with only a brief introduction to statistics, this book takes you on a statistical journey from how polls are taken to how they can—and should—be used to estimate current popular opinion. Once an understanding of the election process is built, we turn toward testing elections for evidence of unfairness. While holding elections has become the de facto proof of government legitimacy, those electoral processes may hide the dirty little secret of the government, illicitly ensuring a favorable election outcome. This book includes these features designed to make your statistical journey more enjoyable: Vignettes of elections, including maps, starting each chapter to motivate the material In-chapter cues to help one avoid the heavy math—or to focus on it End-of-chapter problems designed to review and extend what was covered in the chapter Many opportunities to turn the power of the R Statistical Environment to the enclosed election data files, as well as to those you find interesting The second edition improves upon this and includes: A rewrite of several chapters to make the underlying concepts more clear A chapter dedicated to confidence intervals, what they mean, and what they do not Additional experiments to help you better understand the statistics of elections A new introduction to polling, its terms, its processes, and its ethics From these features, it is clear that the audience for this book is quite diverse. It provides the statistics and mathematics for those interested in statistics and mathematics, but it also provides detours for those who just want a good read and a deeper understanding of elections.

Download or read book The Psychometrics of Standard Setting written by Mark Reckase and published by CRC Press. This book was released on 2023-01-31 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unifying structure for the activities that fall under the process typically called "standard setting" on tests of proficiency. Standard setting refers to the methodology used to identify performance standards on tests of proficiency. The results from standard setting studies are critical for supporting the use of many types of tests. The process is frequently applied to educational, psychological, licensure/certification, and other types of tests and examination systems. The literature on procedures for standard setting is extensive, but the methodology for standard setting has evolved in a haphazard way over many decades without a unifying theory to support the evaluation of the methods and the validation of inferences made from the standards. This text provides a framework for going beyond specific standard setting methods to gain an understanding of the goals for the methods and how to evaluate whether the goals have been achieved. The unifying structure provided in this text considers policy that calls for the existence of performance standards, the relationship of proficiency test design to the policy, and tasks assigned to subject matter experts to help them convert the policy to estimates of locations on the reporting score scale for the test. Guidance is provided for how to connect the psychometric aspects of the standard setting process to the intentions of policy makers as expressed in policy statements. Further, the structure is used support validity arguments for inferences made when using standards. Examples are provided to show how the unifying structure can be used to evaluate and improve standard setting methodology.

Download or read book Multilevel Modeling Using R written by W. Holmes Finch and published by CRC Press. This book was released on 2024-04-05 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like its bestselling predecessor, Multilevel Modeling Using R, Third Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single-level and multilevel data. The third edition of the book includes several new topics that were not present in the second edition. Specifically, a new chapter has been included, focussing on fitting multilevel latent variable modeling in the R environment. With R, it is possible to fit a variety of latent variable models in the multilevel context, including factor analysis, structural models, item response theory, and latent class models. The third edition also includes new sections in Chapter 11 describing two useful alternatives to standard multilevel models, fixed effects models and generalized estimating equations. These approaches are particularly useful with small samples and when the researcher is interested in modeling the correlation structure within higher-level units (e.g., schools). The third edition also includes a new section on mediation modeling in the multilevel context, in Chapter 11. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research.

Download or read book Generalized Kernel Equating with Applications in R written by Marie Wiberg and published by CRC Press. This book was released on 2024-11-01 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons. The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.

Download or read book Intensive Longitudinal Analysis of Human Processes written by Kathleen M. Gates and published by CRC Press. This book was released on 2023-01-31 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on a span of statistical topics relevant to researchers who seek to conduct person-specific analysis of human data. Our purpose is to provide one consolidated resource that includes techniques from disciplines such as engineering, physics, statistics, and quantitative psychology and outlines their application to data often seen in human research. The book balances mathematical concepts with information needed for using these statistical approaches in applied settings, such as interpretative caveats and issues to consider when selecting an approach. The statistical topics covered here include foundational material as well as state-of-the-art methods. These analytic approaches can be applied to a range of data types such as psychophysiological, self-report, and passively collected measures such as those obtained from smartphones. We provide examples using varied data sources including functional MRI (fMRI), daily diary, and ecological momentary assessment data. Features: Description of time series, measurement, model building, and network methods for person-specific analysis Discussion of the statistical methods in the context of human research Empirical and simulated data examples used throughout the book R code for analyses and recorded lectures for each chapter available via a link available at www.routledge.com/9781482230598 Across various disciplines of human study, researchers are increasingly seeking to conduct person-specific analysis. This book provides comprehensive information, so no prior knowledge of these methods is required. We aim to reach active researchers who already have some understanding of basic statistical testing. Our book provides a comprehensive resource for those who are just beginning to learn about person-specific analysis as well as those who already conduct such analysis but seek to further deepen their knowledge and learn new tools.

Download or read book An Introduction to the Rasch Model with Examples in R written by Rudolf Debelak and published by CRC Press. This book was released on 2022-06-07 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to the Rasch Model with Examples in R offers a clear, comprehensive introduction to the Rasch model along with practical examples in the free, open-source software R. It is accessible for readers without a background in psychometrics or statistics, while also providing detailed explanations of the relevant mathematical and statistical concepts for readers who want to gain a deeper understanding. Its worked examples in R demonstrate how to apply the methods to real-world examples and how to interpret the resulting output. In addition to motivating and presenting the Rasch model, the book covers different methods for parameter estimation and for assessing fit and differential item functioning (DIF). While focusing on the Rasch model, it also addresses a variety of other dichotomous and polytomous Rasch and item response theory (IRT) models, such as two-parameter logistic (2PL) and Partial Credit models, and extensions, including mixture Rasch models and computerized adaptive testing (CAT). Theory is presented in a self-contained way. All necessary mathematical and statistical background is contained in the chapters and appendices. The book also provides detailed, step-by-step instructions for getting started with R and using the eRm, mirt, TAM and rstan packages for fitting Rasch models.

Download or read book Data Science for Public Policy written by Jeffrey C. Chen and published by Springer Nature. This book was released on 2021-09-01 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst’s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.

Download or read book Parsing Psychology Statistical and Computational Methods using Physiological Behavioral Social and Cognitive Data written by Pietro Cipresso and published by Frontiers Media SA. This book was released on 2020-02-14 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Download or read book Iterative Regularization Methods for Nonlinear Ill Posed Problems written by Barbara Kaltenbacher and published by Walter de Gruyter. This book was released on 2008-09-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data perturbations. Those problems require a regularization, i.e., a special numerical treatment. This book presents regularization schemes which are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.

Download or read book Global Inequalities Polarization written by M. Mustafa Erdoğdu and published by IJOPEC PUBLICATION. This book was released on 2020-10-10 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inequalities are increasing across the world and living conditions are very unequal between different parts of the world. Some people can live healthy, rich, and happy lives while others continue to live in poor health, poverty, and grief. Inequalities have greatly strengthened the economic and political power of those people at the top. This volume is titled “Global Inequalities and Polarization” and contains eight selected articles that approach inequality and polarization from different angles.

Download or read book Regularization Methods in Banach Spaces written by Thomas Schuster and published by Walter de Gruyter. This book was released on 2012-07-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in a large variety of applications ranging from medical imaging and non-destructive testing via finance to systems biology. Many of these problems belong to the class of parameter identification problems in partial differential equations (PDEs) and thus are computationally demanding and mathematically challenging. Hence there is a substantial need for stable and efficient solvers for this kind of problems as well as for a rigorous convergence analysis of these methods. This monograph consists of five parts. Part I motivates the importance of developing and analyzing regularization methods in Banach spaces by presenting four applications which intrinsically demand for a Banach space setting and giving a brief glimpse of sparsity constraints. Part II summarizes all mathematical tools that are necessary to carry out an analysis in Banach spaces. Part III represents the current state-of-the-art concerning Tikhonov regularization in Banach spaces. Part IV about iterative regularization methods is concerned with linear operator equations and the iterative solution of nonlinear operator equations by gradient type methods and the iteratively regularized Gauß-Newton method. Part V finally outlines the method of approximate inverse which is based on the efficient evaluation of the measured data with reconstruction kernels.