Multilevel Modeling In Plain Language
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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 In Plain Language
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Author : Karen Robson
language : en
Publisher:
Release Date : 2016
Multilevel Modeling In Plain Language written by Karen Robson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Multilevel models (Statistics) 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 In Plain Language
DOWNLOAD
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.
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.
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.
The Multivariate Social Scientist
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Author : Graeme D Hutcheson
language : en
Publisher: SAGE
Release Date : 1999-05-19
The Multivariate Social Scientist written by Graeme D Hutcheson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-19 with Social Science categories.
Starting from simple hypothesis testing and then moving towards model-building, this valuable book takes readers through the basics of multivariate analysis including: which tests to use on which data; how to run analyses in SPSS for Windows and GLIM4; how to interpret results; and how to report and present the reports appropriately. Using a unified conceptual framework (based around the Generalized Linear Model) the authors explain the commonalities and relationships between methods that include both the analysis of categorical and continuous data.
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.
Psychological Statistics And Psychometrics Using Stata
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Author : Scott A. Baldwin
language : en
Publisher:
Release Date : 2019
Psychological Statistics And Psychometrics Using Stata written by Scott A. Baldwin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Psychology categories.
"Psychological statistics and psychometrics using Stata by Scott Baldwin is a complete and concise resource for students and researchers in the behavioral sciences. Professor Baldwin includes dozens of worked examples using real data to illustrate the theory and concepts. This book would be an excellent textbook for a graduate-level course in psychometrics. It is also an ideal reference for psychometricians who are new to Stata. Baldwin's primary goal in this book is to help readers become competent users of statistics. To that end, he first introduces basic statistical methods such as regression, t tests, and ANOVA. He focuses on explaining the models, how they can be used with different types of variables, and how to interpret the results. After building this foundation, Baldwin covers more advanced statistical techniques, including power-and-sample size calculations, multilevel modeling, and structural equation modeling. This book also discusses measurement concepts that are crucial in psychometrics. For instance, Baldwin explores how reliability and validity can be understood and evaluated using exploratory and confirmatory factor analysis. Baldwin includes dozens of worked examples using real data to illustrate the theory and concepts. In addition to teaching statistical topics, this book helps readers become proficient Stata users. Baldwin teaches Stata basics ranging from navigating the interface to using features for data management, descriptive statistics, and graphics. He emphasizes the need for reproducibility in data analysis; therefore, he is careful to explain how version control and do-files can be used to ensure that results are reproducible. As each statistical concept is introduced, the corresponding commands for fitting and interpreting models are demonstrated. Beyond this, readers learn how to run simulations in Stata to help them better understand the models they are fitting and other statistical concepts. This book is an excellent textbook for graduate-level courses in psychometrics. It is also an ideal reference for psychometricians and other social scientists who are new to Stata"--Publisher's website.
Applied Regression Modeling
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Author : Iain Pardoe
language : en
Publisher: John Wiley & Sons
Release Date : 2013-01-07
Applied Regression Modeling written by Iain Pardoe 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 2013-01-07 with Mathematics categories.
Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
Multilevel Modeling
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Author : G. David Garson
language : en
Publisher: SAGE Publications
Release Date : 2019-07-31
Multilevel Modeling written by G. David Garson and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-31 with Education categories.
Providing a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences.