Download or read book Interpreting and Visualizing Regression Models Using Stata written by MICHAEL N. MITCHELL and published by Stata Press. This book was released on 2020-12-18 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Interpreting and Visualizing Regression Models Using Stata written by Michael N. Mitchell and published by . This book was released on 2012 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Event History Analysis With Stata" provides an introduction to event history modeling techniques using Stata (version 9), a widely used statistical program that provides tools for data analysis. The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data, to data organization, to applications using the software, to the interpretation of results. The book also demonstrates, through example, how to implement hypotheses tests and how to choose the right model. The strengths and limitations of various techniques are emphasized in each example, along with an introduction to the model, details on how to input data, and the related Stata commands. Each application is accompanied by a brief explanation of the underlying statistical concept. Readers are offered the unique opportunity to easily run and modify all of the book's application examples on a computer, by visiting the author's Web site and includes survival rates of patients in medical studies; unemployment periods in economic studies; and the time it takes a criminal to break the law after his release in a criminological study. This new book supplements "Event History Analysis", by Blossfeld et al, and "Techniques of Event History Modeling", by Blossfeld and Rohwer, extending on their coverage of practical applications and statistical theory. Intended for researchers in a variety of fields such as statistics, economics, psychology, sociology, and political science, "Event History Analysis With Stata" also serves as a text, in combination with the authors' other two books, for courses on event history analysis.
Download or read book Interpreting and Visualizing Regression Models Using Stata written by Michael N. Mitchell and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Visual Guide to Stata Graphics Second Edition written by Michael N. Mitchell and published by Stata Press. This book was released on 2008-06-04 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Power of Stata Graphics at Your Fingertips Whether you are new to Stata graphics or a seasoned veteran, this book teaches you how to use Stata to make high-quality graphs that stand out and enhance statistical results. With over 900 illustrated examples and quick-reference tabs, it offers a guide to creating and customizing graphs for any type of statistical data using either Stata commands or the Graph Editor. The author displays each graph example in full color with simple and clear instructions. He shows how to produce various types of graph elements, including marker symbols, lines, legends, captions, titles, axis labels, and grid lines. Reflecting the new graphics features of Stata, this thoroughly updated and expanded edition contains a new chapter that explains how to exploit the power of the new Graph Editor. This edition also includes additional examples and illustrates nearly every example with the Graph Editor.
Download or read book Data Management Using Stata written by Michael N Mitchell and published by Stata Press. This book was released on 2020-06-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.
Download or read book A Practical Introduction to Regression Discontinuity Designs written by Matias D. Cattaneo and published by Cambridge University Press. This book was released on 2024-04-11 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this Element, which continues our discussion in Foundations, the authors provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. The focus is on extensions to the canonical sharp RD setup that we discussed in Foundations. The discussion covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.
Download or read book Stata for the Behavioral Sciences written by Michael N. Mitchell and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stata for the Behavioral Sciences, by Michael Mitchell, is the ideal reference for researchers using Stata to fit ANOVA models and other models commonly applied to behavioral science data. Drawing on his education in psychology and his experience in consulting, Mitchell uses terminology and examples familiar to he reader as he demonstrates how to fit a variety of models, how to interpret results, how to understand simple and interaction effects, and how to explore results graphically. Although this book is not designed as an introduction to Stata, it is appealing even to Stata novices. Throughout the text, Mitchell thoughtfully addresses any features of Stata that are important to understand for the analysis at hand. He also is careful to point out additional resources such as related videos from Stata's YouTube channel. This book is an easy-to-follow guide to analyzing data using Stata for researchers in the behavioral sciences and a valuable addition to the bookshelf of anyone interested in applying ANOVA methods to a variety of experimental designs.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Egocentric Network Analysis written by Brea L. Perry and published by Structural Analysis in the Soc. This book was released on 2018-03-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.
Download or read book Modeling and Interpreting Interactive Hypotheses in Regression Analysis written by Robert Franzese and published by University of Michigan Press. This book was released on 2009-09-23 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social scientists study complex phenomena about which they often propose intricate hypotheses tested with linear-interactive or multiplicative terms. While interaction terms are hardly new to social science research, researchers have yet to develop a common methodology for using and interpreting them. Modeling and Interpreting Interactive Hypotheses in Regression Analysis provides step-by-step guidance on how to connect substantive theories to statistical models and how to interpret and present the results. "Kam and Franzese is a must-have for all empirical social scientists interested in teasing out the complexities of their data." ---Janet M. Box-Steffensmeier, Ohio State University "Kam and Franzese have written what will become the definitive source on dealing with interaction terms and testing interactive hypotheses. It will serve as the standard reference for political scientists and will be one of those books that everyone will turn to when helping our students or doing our work. But more than that, this book is the best text I have seen for getting students to really think about the importance of careful specification and testing of their hypotheses." ---David A. M. Peterson, Texas A&M University "Kam and Franzese have given scholars and teachers of regression models something they've needed for years: a clear, concise guide to understanding multiplicative interactions. Motivated by real substantive examples and packed with valuable examples and graphs, their book belongs on the shelf of every working social scientist." ---Christopher Zorn, University of South Carolina "Kam and Franzese make it easy to model what good researchers have known for a long time: many important and interesting causal effects depend on the presence of other conditions. Their book shows how to explore interactive hypotheses in your own research and how to present your results. The book is straightforward yet technically sophisticated. There are no more excuses for misunderstanding, misrepresenting, or simply missing out on interaction effects!" ---Andrew Gould, University of Notre Dame Cindy D. Kam is Assistant Professor, Department of Political Science, University of California, Davis. Robert J. Franzese Jr. is Associate Professor, Department of Political Science, University of Michigan, and Research Associate Professor, Center for Political Studies, Institute for Social Research, University of Michigan. For datasets, syntax, and worksheets to help readers work through the examples covered in the book, visit: www.press.umich.edu/KamFranzese/Interactions.html
Download or read book Regression and Other Stories written by Andrew Gelman and published by Cambridge University Press. This book was released on 2020-07-23 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.
Download or read book Discovering Structural Equation Modeling Using Stata 13 Revised Edition written by Alan C. Acock and published by Stata Press. This book was released on 2013-09-10 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning. A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.
Download or read book Discovering Partial Least Squares with JMP written by Ian Cox and published by SAS Institute. This book was released on 2013-10 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores Partial Least Squares and positions it within the more general context of multivariate analysis. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.
Download or read book Multilevel Modeling in Plain Language written by Karen Robson and published by SAGE. This book was released on 2015-11-02 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Introducing Survival and Event History Analysis written by Melinda Mills and published by SAGE. This book was released on 2011-01-19 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.
Download or read book Introduction to Mediation Moderation and Conditional Process Analysis Second Edition written by Andrew F. Hayes and published by Guilford Publications. This book was released on 2017-10-30 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Introduction to Mediation, Moderation, and Conditional Process Analysis, Third Edition, ISBN 978-1-4625-4903-0.
Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
