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Multilevel And Longitudinal Modeling Using Stata Second Edition
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Book Synopsis Multilevel and Longitudinal Modeling Using Stata, Second Edition by : Sophia Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata, Second Edition written by Sophia Rabe-Hesketh and published by Stata Press. This book was released on 2008-02-07 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook looks specifically at Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables.
Book Synopsis Multilevel and Longitudinal Modeling Using Stata, Volumes I and II by : S. Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata, Volumes I and II written by S. Rabe-Hesketh and published by . This book was released on 2021-10-22 with total page 1098 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Multilevel and Longitudinal Modeling Using Stata, Fourth Edition discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients in hospitals, or employees in firms. Longitudinal data are also clustered with, for instance, repeated measurements on patients or several panel waves per survey respondent. Multilevel and longitudinal modeling can exploit the richness of such data and can disentangle processes operating at different levels. Assuming some knowledge of linear regression, this bestseller explains models and their assumptions, applies methods to real data using Stata, and shows how to interpret the results. Across volumes, the 16 chapters, over 140 exercises, and over 110 datasets span a wide range of disciplines, making the book suitable for courses in the medical, social, and behavioral sciences and in applied statistics. This first volume is dedicated to models for continuous responses and is a prerequisite for the second volume on models for other response types. It has been thoroughly revised and updated for Stata 16. New material includes the Kenward-Roger degree-of-freedom correction for improved inference with a small number of clusters, difference-in-differences estimation for natural experiments, and instrumental-variable estimation to handle level-1 endogeneity"--
Book Synopsis Multilevel and Longitudinal Modeling Using Stata by : S. Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata written by S. Rabe-Hesketh and published by . This book was released on 2022 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multilevel and Longitudinal Modeling Using Stata by : Sophia Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata written by Sophia Rabe-Hesketh and published by Stata Press. This book was released on 2012-04-02 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume II is devoted to generalized linear mixed models for binary, categorical, count, and survival outcomes. The second volume has seven chapters also organized in four parts. The first three parts in volume II cover models for categorical responses, including binary, ordinal, and nominal (a new chapter); models for count data; and models for survival data, including discrete-time and continuous-time (a new chapter) survival responses. The final part in volume II describes models with nested and crossed-random effects with an emphasis on binary outcomes.
Book Synopsis Multilevel and Longitudinal Modeling Using Stata: Categorical responses, counts, and survival by : S. Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata: Categorical responses, counts, and survival written by S. Rabe-Hesketh and published by . This book was released on 2012 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Multilevel and Longitudinal Modeling Using Stata, Third Edition, discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients nested in hospitals, or employees nested in firms. Longitudinal data are also clustered with, for instance, repeated measurements on patients or several panel waves per survey respondent. Multilevel and longitudinal modeling can exploit the richness of such data and can disentangle processes operating at different levels. Assuming some knowledge of linear regression, this bestseller explains models and their assumptions, applies methods to real data using Stat, and shows how to interpret the results. Across volume, the 16 chapters and 144 exercises are based on the 110 datasets that span a wide range of disciplines, making the book suitable for courses in the medical, social, and behavioral sciences, and in applied statistics. Th[e] first volume is dedicated to models for continuous responses and is a prerequisite for the second volume on models for other response types. It contains two new chapters on longitudinal data, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12. Following volume I on models for continuous responses, th[e] second volume covers models for all other important response types: binary, ordinal, and nominal (discrete choice) responses; counts; and discrete-time and continuous-time survival (durations). It contains three new chapters, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12"--Covers.
Book Synopsis Multilevel and Longitudinal Modeling Using Stata by : Sophia Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata written by Sophia Rabe-Hesketh and published by Stata Press. This book was released on 2012-04-02 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume I is devoted to continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. The first part provides a review of the methods of linear regression. The second part provides an in-depth coverage of the two-level models, the simplest extensions of a linear regression model. The mixed-model foundation and the in-depth coverage of the mixed-model principles provided in volume I for continuous outcomes, make it straightforward to transition to generalized linear mixed models for noncontinuous outcomes described in volume II.
Book Synopsis Multilevel and Longitudinal Modeling Using Stata, Volumes I and II, Third Edition by : Sophia Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata, Volumes I and II, Third Edition written by Sophia Rabe-Hesketh and published by Stata Press. This book was released on 2012-04-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines Stata's treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables. Volume I covers continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. Volume II discusses generalized linear mixed models for binary, categorical, count, and survival outcomes.
Book Synopsis A Gentle Introduction to Stata, Second Edition by : Alan C. Acock
Download or read book A Gentle Introduction to Stata, Second Edition written by Alan C. Acock and published by Stata Press. This book was released on 2008-09-03 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A Gentle Introduction to Stata, Second Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will not only be able to use Stata well but also learn new aspects of Stata easily. Acock assumes that the user is not familiar with any statistical software. This assumption of a blank slate is central to the structure and contents of the book. Acock starts with the basics; for example, the portion of the book that deals with data management begins with a careful and detailed example of turning survey data on paper into a Stata-ready dataset on the computer. When explaining how to go about basic exploratory statistical procedures, Acock includes notes that should help the reader develop good work habits. This mixture of explaining good Stata habits and good statistical habits continues throughout the book. Acock is quite careful to teach the reader all aspects of using Stata. He covers data management, good work habits (including the use of basic do-files), basic exploratory statistics (including graphical displays), and analyses using the standard array of basic statistical tools (correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion). Acock teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. In this way, he ensures that all types of users can build good work habits. Each chapter has exercises that the motivated reader can use to reinforce the material. The tone of the book is friendly and conversational without ever being glib or condescending. Important asides and notes about terminology are set off in boxes, which makes the text easy to read without any convoluted twists or forward-referencing. Rather than splitting topics by their Stata implementation, Acock chose to arrange the topics as they would be in a basic statistics textbook; graphics and postestimation are woven into the material in a natural fashion. Real datasets, such as the General Social Surveys from 2002 and 2006, are used throughout the book. The focus of the book is especially helpful for those in psychology and the social sciences, because the presentation of basic statistical modeling is supplemented with discussions of effect sizes and standardized coefficients. Various selection criteria, such as semipartial correlations, are discussed for model selection. The second edition of the book has been updated to reflect new features in Stata 10 and includes a new chapter on the use of factor analysis to develop valid, reliable scale measures."--Publisher's website.
Book Synopsis Multilevel Modeling by : Douglas A. Luke
Download or read book Multilevel Modeling written by Douglas A. Luke and published by SAGE Publications. This book was released on 2019-12-13 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the basic approach to estimating and evaluating a two-level model; discusses the major extensions to mixed-effects models; and provides advice for where to go for instruction in more advanced techniques. Rich with examples, the Second Edition expands coverage of longitudinal methods, diagnostic procedures, models of counts (Poisson), power analysis, cross-classified models, and adds a new section added on presenting modeling results. A website for the book includes the data and the statistical code (both R and Stata) used for all of the presented analyses.
Book Synopsis Multilevel and Longitudinal Modeling Using Stata by : S. Rabe-Hesketh
Download or read book Multilevel and Longitudinal Modeling Using Stata written by S. Rabe-Hesketh and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multilevel and Longitudinal Modeling with IBM SPSS by : Ronald H. Heck
Download or read book Multilevel and Longitudinal Modeling with IBM SPSS written by Ronald H. Heck and published by Routledge. This book was released on 2013-08-22 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED). Annotated screen shots provide readers with a step-by-step understanding of each technique and navigating the program. Readers learn how to set up, run, and interpret a variety of models. Diagnostic tools, data management issues, and related graphics are introduced throughout. Annotated syntax is also available for those who prefer this approach. Extended examples illustrate the logic of model development to show readers the rationale of the research questions and the steps around which the analyses are structured. The data used in the text and syntax examples are available at www.routledge.com/9780415817110. Highlights of the new edition include: Updated throughout to reflect IBM SPSS Version 21. Further coverage of growth trajectories, coding time-related variables, covariance structures, individual change and longitudinal experimental designs (Ch.5). Extended discussion of other types of research designs for examining change (e.g., regression discontinuity, quasi-experimental) over time (Ch.6). New examples specifying multiple latent constructs and parallel growth processes (Ch. 7). Discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures (Ch.1). The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques which facilitate working with multilevel, longitudinal, and cross-classified data sets. Chapters 3 and 4 introduce the basics of multilevel modeling: developing a multilevel model, interpreting output, and trouble-shooting common programming and modeling problems. Models for investigating individual and organizational change are presented in chapters 5 and 6, followed by models with multivariate outcomes in chapter 7. Chapter 8 provides an illustration of multilevel models with cross-classified data structures. The book concludes with ways to expand on the various multilevel and longitudinal modeling techniques and issues when conducting multilevel analyses. It's ideal for courses on multilevel and longitudinal modeling, multivariate statistics, and research design taught in education, psychology, business, and sociology.
Book Synopsis Generalized Estimating Equations, Second Edition by : James W. Hardin
Download or read book Generalized Estimating Equations, Second Edition written by James W. Hardin and published by CRC Press. This book was released on 2012-12-10 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined. Stata is used as the primary software for running and displaying modeling output; associated R code is also given to allow R users to replicate Stata examples. Specific examples of SAS usage are provided in the final chapter as well as on the book’s website. This second edition incorporates comments and suggestions from a variety of sources, including the Statistics.com course on longitudinal and panel models taught by the authors. Other enhancements include an examination of GEE marginal effects; a more thorough presentation of hypothesis testing and diagnostics, covering competing hierarchical models; and a more detailed examination of previously discussed subjects. Along with doubling the number of end-of-chapter exercises, this edition expands discussion of various models associated with GEE, such as penalized GEE, cumulative and multinomial GEE, survey GEE, and quasi-least squares regression. It also offers a thoroughly new presentation of model selection procedures, including the introduction of an extension to the QIC measure that is applicable for choosing among working correlation structures. See Professor Hilbe discuss the book.
Book Synopsis Applied Ordinal Logistic Regression Using Stata by : Xing Liu
Download or read book Applied Ordinal Logistic Regression Using Stata written by Xing Liu and published by SAGE Publications. This book was released on 2015-09-30 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata by Xing Liu helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.
Book Synopsis Handbook of Item Response Theory by : Wim J. van der Linden
Download or read book Handbook of Item Response Theory written by Wim J. van der Linden and published by CRC Press. This book was released on 2018-02-19 with total page 1584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.
Book Synopsis Multilevel Analysis by : Joop J. Hox
Download or read book Multilevel Analysis written by Joop J. Hox and published by Routledge. This book was released on 2010-09-13 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.
Book Synopsis Multilevel and Longitudinal Modeling with IBM SPSS by : Ronald H. Heck
Download or read book Multilevel and Longitudinal Modeling with IBM SPSS written by Ronald H. Heck and published by Routledge. This book was released on 2022-04-11 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel and Longitudinal Modeling with IBM SPSS, Third Edition, demonstrates how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Versions 25-27. Annotated screenshots with all relevant output provide readers with a step-by-step understanding of each technique as they are shown how to navigate the program. Throughout, diagnostic tools, data management issues, and related graphics are introduced. SPSS commands show the flow of the menu structure and how to facilitate model building, while annotated syntax is also available for those who prefer this approach. Extended examples illustrating the logic of model development and evaluation are included throughout the book, demonstrating the context and rationale of the research questions and the steps around which the analyses are structured. The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques that facilitate working with multilevel, longitudinal, or cross-classified data sets. The next few chapters introduce the basics of multilevel modeling, developing a multilevel model, extensions of the basic two-level model (e.g., three-level models, models for binary and ordinal outcomes), and troubleshooting techniques for everyday-use programming and modeling problems along with potential solutions. Models for investigating individual and organizational change are next developed, followed by models with multivariate outcomes and, finally, models with cross-classified and multiple membership data structures. The book concludes with thoughts about ways to expand on the various multilevel and longitudinal modeling techniques introduced and issues (e.g., missing data, sample weights) to keep in mind in conducting multilevel analyses. Key features of the third edition: Thoroughly updated throughout to reflect IBM SPSS Versions 26-27. Introduction to fixed-effects regression for examining change over time where random-effects modeling may not be an optimal choice. Additional treatment of key topics specifically aligned with multilevel modeling (e.g., models with binary and ordinal outcomes). Expanded coverage of models with cross-classified and multiple membership data structures. Added discussion on model checking for improvement (e.g., examining residuals, locating outliers). Further discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures. Supported by online data sets, the book's practical approach makes it an essential text for graduate-level courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in departments of business, education, health, psychology, and sociology. The book will also prove appealing to researchers in these fields. The book is designed to provide an excellent supplement to Heck and Thomas's An Introduction to Multilevel Modeling Techniques, Fourth Edition; however, it can also be used with any multilevel or longitudinal modeling book or as a stand-alone text.
Book Synopsis Quantitative Studies in Green and Conservation Criminology by : Michael J. Lynch
Download or read book Quantitative Studies in Green and Conservation Criminology written by Michael J. Lynch and published by Routledge. This book was released on 2019-07-17 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the early development and throughout the short history of green/conservation criminology, limited attention has been directed toward quantitative analyses of relevant environmental crime, law and justice concerns. While recognizing the importance of establishing a theory and terminology in the early stages of development, this book redresses this imbalance. The work features contributions that undertake empirical quantitative studies of green/conservation crime and justice issues by both conservation and green criminologists. The collection highlights the shared concerns of these groups within important forms of ecological crime and victimization, and illustrates the ways in which these approaches can be undertaken quantitatively. It includes quantitative conservation/green criminological studies that represent the work of both well-established scholars in these fields, along with studies by scholars whose works are less well-known and who are also contributing to shaping this area of research. The book presents a valuable contribution to the areas of Green and Conservation Criminology. It will appeal to academics and students working in these areas.
