Multilevel And Longitudinal Modeling Using Stata Second Edition
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Multilevel And Longitudinal Modeling Using Stata Second Edition
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Author : Sophia Rabe-Hesketh
language : en
Publisher: Stata Press
Release Date : 2008-02-07
Multilevel And Longitudinal Modeling Using Stata Second Edition written by Sophia Rabe-Hesketh and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-07 with Computers categories.
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.
Interpreting And Visualizing Regression Models Using Stata
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Author : MICHAEL N. MITCHELL
language : en
Publisher: Stata Press
Release Date : 2020-12-18
Interpreting And Visualizing Regression Models Using Stata written by MICHAEL N. MITCHELL and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with categories.
Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.
Multilevel Modeling In Plain Language
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Author : Karen Robson
language : en
Publisher: SAGE
Release Date : 2015-11-02
Multilevel Modeling In Plain Language written by Karen Robson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-02 with Social Science categories.
Have you been told you need to do multilevel modeling, but you can′t get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense? Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated. This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.
Multilevel Modeling
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Author : Douglas A. Luke
language : en
Publisher: SAGE
Release Date : 2004-07-08
Multilevel Modeling written by Douglas A. Luke and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-08 with Mathematics categories.
Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.
Handbook Of Statistical Analyses Using Stata
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Author : Brian S. Everitt
language : en
Publisher: CRC Press
Release Date : 2006-11-15
Handbook Of Statistical Analyses Using Stata written by Brian S. Everitt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-15 with Mathematics categories.
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Multilevel Analysis
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Author : Tom A. B. Snijders
language : en
Publisher: SAGE
Release Date : 1999
Multilevel Analysis written by Tom A. B. Snijders and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
Applied Ordinal Logistic Regression Using Stata
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Author : Xing Liu
language : en
Publisher: SAGE Publications
Release Date : 2015-09-30
Applied Ordinal Logistic Regression Using Stata 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 2015-09-30 with Social Science categories.
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 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. An open-access website for the book contains data sets, Stata code, and answers to in-text questions.
Multilevel And Longitudinal Modeling Using Stata
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Author : S. Rabe-Hesketh
language : en
Publisher:
Release Date : 2022
Multilevel And Longitudinal Modeling Using Stata written by S. Rabe-Hesketh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Linear Mixed Models
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Author : Brady T. West
language : en
Publisher: CRC Press
Release Date : 2014-07-17
Linear Mixed Models written by Brady T. West and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-17 with Mathematics categories.
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM. New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggested approaches to writing simulations Use of the lmer() function in the lme4 R package New sections on fitting LMMs to complex sample survey data and Bayesian approaches to making inferences based on LMMs Updated graphical procedures in the software packages Substantially revised index to enable more efficient reading and easier location of material on selected topics or software options More practical recommendations on using the software for analysis A new R package (WWGbook) that contains all of the data sets used in the examples Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.
Hierarchical Linear Modeling
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Author : G. David Garson
language : en
Publisher: SAGE
Release Date : 2013
Hierarchical Linear Modeling written by G. David Garson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.