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Regression Models For Categorical Count And Related Variables


Regression Models For Categorical Count And Related Variables
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Regression Models For Categorical Count And Related Variables


Regression Models For Categorical Count And Related Variables
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Author : John P. Hoffmann
language : en
Publisher: Univ of California Press
Release Date : 2016-08-16

Regression Models For Categorical Count And Related Variables written by John P. Hoffmann and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-16 with Mathematics categories.


Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes—all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book.



Categorical Data Analysis And Multilevel Modeling Using R


Categorical Data Analysis And Multilevel Modeling Using R
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Author : Xing Liu
language : en
Publisher: SAGE Publications
Release Date : 2022-02-25

Categorical Data Analysis And Multilevel Modeling Using R written by Xing Liu and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Social Science categories.


Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.



Regression Analysis By Example Using R


Regression Analysis By Example Using R
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Author : Ali S. Hadi
language : en
Publisher: John Wiley & Sons
Release Date : 2023-10-31

Regression Analysis By Example Using R written by Ali S. Hadi 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 2023-10-31 with Mathematics categories.


Regression Analysis By Example Using R A STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSIS In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R. Readers will also find: Reorganized, expanded, and upgraded exercises at the end of each chapter with an emphasis on data analysis Updated data sets and examples throughout the book Complimentary access to a companion website that provides data sets in xlsx, csv, and txt format Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.



Applied Regression Models In The Social Sciences


Applied Regression Models In The Social Sciences
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Author : Dudley L. Poston, Jr
language : en
Publisher: Cambridge University Press
Release Date : 2023-08-17

Applied Regression Models In The Social Sciences written by Dudley L. Poston, Jr and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Social Science categories.


This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.



Linear Regression Models


Linear Regression Models
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Author : John P. Hoffmann
language : en
Publisher: CRC Press
Release Date : 2021-09-12

Linear Regression Models written by John P. Hoffmann and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-12 with Mathematics categories.


Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to determine whether they are satisfied and how to modify the regression model if they are not. The book also includes chapters on specifying the correct model, adjusting for measurement error, understanding the effects of influential observations, and using the model with multilevel data. The concluding chapter presents an alternative model—logistic regression—designed for binary or two-category outcome variables. The book includes appendices that discuss data management and missing data and provides simulations in R to test model assumptions. Features Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied. Uses numerous graphs in R to illustrate the model’s results, assumptions, and other features. Does not assume a background in calculus or linear algebra, rather, an introductory statistics course and familiarity with elementary algebra are sufficient. Provides many examples using real-world datasets relevant to various academic disciplines. Fully integrates the R software environment in its numerous examples. The book is aimed primarily at advanced undergraduate and graduate students in social, behavioral, health sciences, and related disciplines, taking a first course in linear regression. It could also be used for self-study and would make an excellent reference for any researcher in these fields. The R code and detailed examples provided throughout the book equip the reader with an excellent set of tools for conducting research on numerous social and behavioral phenomena. John P. Hoffmann is a professor of sociology at Brigham Young University where he teaches research methods and applied statistics courses and conducts research on substance use and criminal behavior.



Quantitative Epidemiology


Quantitative Epidemiology
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Author : Xinguang Chen
language : en
Publisher: Springer Nature
Release Date : 2022-02-22

Quantitative Epidemiology written by Xinguang Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Mathematics categories.


This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis.



Scientific Data Analysis With R


Scientific Data Analysis With R
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Author : Azizur Rahman
language : en
Publisher: CRC Press
Release Date : 2024-11-28

Scientific Data Analysis With R written by Azizur Rahman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-28 with Mathematics categories.


In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets. This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry data. Key Features: Presents contemporary concepts of data science and biostatistics with real-life data analysis examples Promotes the evolution of fundamental and advanced methods applying to real-life problem-solving cases Explores computational statistical data science techniques from initial conception to recent developments of biostatistics Provides all R codes and real-world datasets to practice and competently apply into reader’s own domains Written in an exclusive state-of-the-art deductive approach without any theoretical hitches to support all contemporary readers



Analyzing Categorical Data


Analyzing Categorical Data
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Author : Jeffrey S. Simonoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-05

Analyzing Categorical Data written by Jeffrey S. Simonoff 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 2013-06-05 with Social Science categories.


Categorical data arise often in many fields, including biometrics, economics, management, manufacturing, marketing, psychology, and sociology. This book provides an introduction to the analysis of such data. The coverage is broad, using the loglinear Poisson regression model and logistic binomial regression models as the primary engines for methodology. Topics covered include count regression models, such as Poisson, negative binomial, zero-inflated, and zero-truncated models; loglinear models for two-dimensional and multidimensional contingency tables, including for square tables and tables with ordered categories; and regression models for two-category (binary) and multiple-category target variables, such as logistic and proportional odds models. All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the context and background of the problem, model checking, and scientific implications. More than 200 exercises are provided, many also based on recent subject area literature. Data sets and computer code are available at a web site devoted to the text. Adopters of this book may request a solutions manual from: [email protected]. From the reviews: "Jeff Simonoff's book is at the top of the heap of categorical data analysis textbooks...The examples are superb. Student reactions in a class I taught from this text were uniformly positive, particularly because of the examples and exercises. Additional materials related to the book, particularly code for S-Plus, SAS, and R, useful for analysis of examples, can be found at the author's Web site at New York University. I liked this book for this reason, and recommend it to you for pedagogical purposes." (Stanley Wasserman, The American Statistician, August 2006, Vol. 60, No. 3) "The book has various noteworthy features. The examples used are from a variety of topics, including medicine, economics, sports, mining, weather, as well as social aspects like needle-exchange programs. The examples motivate the theory and also illustrate nuances of data analytical procedures. The book also incorporates several newer methods for analyzing categorical data, including zero-inflated Poisson models, robust analysis of binomial and poisson models, sandwich estimators, multinomial smoothing, ordinal agreement tables...this is definitely a good reference book for any researcher working with categorical data." Technometrics, May 2004 "This guide provides a practical approach to the appropriate analysis of categorical data and would be a suitable purchase for individuals with varying levels of statistical understanding." Paediatric and Perinatal Epidemiology, 2004, 18 "This book gives a fresh approach to the topic of categorical data analysis. The presentation of the statistical methods exploits the connection to regression modeling with a focus on practical features rather than formal theory...There is much to learn from this book. Aside from the ordinary materials such as association diagrams, Mantel-Haenszel estimators, or overdispersion, the reader will also find some less-often presented but interesting and stimulating topics...[T]his is an excellent book, giving an up-to-date introduction to the wide field of analyzing categorical data." Biometrics, September 2004 "...It is of great help to data analysts, practitioners and researchers who deal with categorical data and need to get a necessary insight into the methods of analysis as well as practical guidelines for solving problems." International Journal of General Systems, August 2004 "The author has succeeded in writing a useful and readable textbook combining most of general theory and practice of count data." Kwantitatieve Methoden "The book especially stresses how to analyze and interpret data...In fact, the highly detailed multi-page descriptions of analysis and interpretation make the book stand out." Mathematical Geology, February 2005 "Overall, this is a competent and detailed text that I would recommend to anyone dealing with the analysis of categorical data." Journal of the Royal Statistical Society "This important work allows for clear analogies between the well-known linear models for Gaussian data and categorical data problems. ... Jeffrey Simonoff’s Analyzing Categorical Data provides an introduction to many of the important ideas and methods for understanding counted data and tables of counts. ... Some readers will find Simonoff’s style very much to their liking due to reliance on extended real data examples to illuminate ideas. ... I think the extensive examples will appeal to most students." (Sanford Weisberg, SIAM Review, Vol. 47 (4), 2005) "It is clear that the focus of Simonoff’s book is different from other books on categorical data analysis. ... As an introductory textbook, the book is comprehensive enough since all basic topics in categorical data analysis are discussed. ... I think Simonoff’s book is a valuable addition to the literature because it discusses important models for counts ... ." (Jeroen K. Vermunt, Statistics in Medicine, Vol. 24, 2005) "The author based this book on his notes for a class with a very diverse pool of students. The material is presented in such a way that a very heterogeneous group of students could grasp it. All methods are illustrated with analyses of real data examples. The author provides a detailed discussion of the context and background of the problem. ... The book is very interesting and can be warmly recommended to people working with categorical data." (EMS - European Mathematical Society Newsletter, December,2004) "Categorical data arise often in many fields ... . This book provides an introduction to the analysis of such data. ... All methods are illustrated with analyses of real data examples, many from recent subject-area journal articles. These analyses are highlighted in the text and are more detailed than is typical ... . More than 200 exercises are provided, including many based on recent subject-area literature. Data sets and computer code are available at a Web site devoted to this text." (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2003) "This book grew out of notes prepared by the author for classes in categorical data analysis. The presentation is fresh and compelling to read. Regression ideas are used to motivate the modelling presented. The book focuses on applying methods to real problems; many of these will be novel to readers of statistics texts ... . All chapters end with a section providing references to books or articles for the inquiring reader." (C.M. O’Brien, Short Book Reviews, Vol. 23 (3), 2003)



International Encyclopedia Of Political Science


International Encyclopedia Of Political Science
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Author : Bertrand Badie
language : en
Publisher: SAGE Publications
Release Date : 2011-09-07

International Encyclopedia Of Political Science written by Bertrand Badie and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-07 with Political Science categories.


Request a FREE 30-day online trial to this title at www.sagepub.com/freetrial With entries from leading international scholars from around the world, this eight-volume encyclopedia offers the widest possible coverage of key areas both regionally and globally. The International Encyclopedia of Political Science provides a definitive, comprehensive picture of all aspects of political life, recognizing the theoretical and cultural pluralism of our approaches and including findings from the far corners of the world. The eight volumes cover every field of politics, from political theory and methodology to political sociology, comparative politics, public policies, and international relations. Entries are arranged in alphabetical order, and a list of entries by subject area appears in the front of each volume for ease of use. The encyclopedia contains a detailed index as well as extensive bibliographical references. Filling the need for an exhaustive overview of the empirical findings and reflections on politics, this reference resource is suited for undergraduate or graduate students who wish to be informed effectively and quickly on their field of study, for scholars seeking information on relevant research findings in their area of specialization or in related fields, and for lay readers who may lack a formal background in political science but have an interest in the field nonetheless. The International Encyclopedia of Political Science provides an essential, authoritative guide to the state of political science at the start of the 21st century and for decades to come, making it an invaluable resource for a global readership, including researchers, students, citizens, and policy makers. The encyclopedia was developed in partnership with the International Political Science Association. Key Themes: Case and Area Studies Comparative Politics, Theory, and Methods Democracy and Democratization Economics Epistemological Foundations Equality and Inequality Gender and Race/Ethnicity International Relations Local Government Peace, War, and Conflict Resolution People and Organizations Political Economy Political Parties Political Sociology Public Policy and Administration Qualitative Methods Quantitative Methods Religion



Sexual And Gender Minority Health


Sexual And Gender Minority Health
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Author : Brea L. Perry
language : en
Publisher: Emerald Group Publishing
Release Date : 2021-01-15

Sexual And Gender Minority Health written by Brea L. Perry and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-15 with Social Science categories.


This volume of Advances in Medical Sociology showcases rich theoretical and empirical contributions on SGM health and wellbeing. The chapters address a variety of topics, drawing from classic and contemporary sociological frameworks and constructs, and reflecting intersecting interdisciplinary approaches to SGM health.