Description: Applied Ordinal Logistic Regression Using Stata by Xing Liu Provides a unified framework for both single-level and multilevel modeling of ordinal categorical data FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description This book 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. Author Biography Xing Liu Ph.D., is a professor of educational research and assessment at Eastern Connecticut State University. He received his Ph.D. in measurement, evaluation, and assessment in the field of educational psychology from the University of Connecticut, Storrs. His interests include categorical data analysis, multilevel modeling, longitudinal data analysis, structural equation modeling, educational assessment, propensity score methods, data science, and Bayesian methods. He is the author of Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel Modeling (2016). His major publications focus on advanced statistical models. His articles have been recognized among the most popular papers published in the Journal of Modern Applied Statistical Methods (JMASM). Dr. Liu is the recipient of the Excellence Award in Creativity/Scholarship at Eastern Connecticut State University. Table of Contents 1. Stata BasicsIntroduction to StataData ManagementGraphsA Summary of Stata Commands in this ChapterExercises2. Review of Basic StatisticsUnderstand Your Data Using Descriptive StatisticsDescriptive Statistics for Continuous Variables Using StataFrequency Distribution for Categorical Variables Using StataIndependent Samples t-test Using StataPaired Samples t-testAnalysis of Variance (ANOVA)CorrelationSimple Linear RegressionMultiple Linear RegressionChi-Square TestMaking Publication-Quality Tables Using StataGeneral Guidelines for Reporting ResutlsA Summary of Stata Commands in this ChapterExercises3. Logistic Regression for Binary DataLogistic Regression Models: An IntroductionResearch Example and Description of the Data and SampleLogistic Regression with Stata: Commands and OutputSummary of Stata Commands in this ChapterExercises4. Proportional Odds Models for Ordinal Response VariablesProportional Odds Models: An IntroductionResearch Example and Description of the Data and SampleProportional Odds Models with Stata: Commands and OutputSummary of Stata Commands in this ChapterExercises5. Partial Proportional Odds Models and Generalized Ordinal Logistic Regression ModelsIntroductionResearch Example and Description of the Data and SamplePartial Proportional Odds Models with Stata: Commands and OutputGeneralized Ordinal Logistic Regression Models with Stata: An ExampleMaking Publication-Quality TablesPresenting the ResultsSummary of Stata Commands in this ChapterExercises6. Continuation Ratio ModelsContinuation Ratio Models: An IntroductionResearch Example and Description of the Data and SampleContinuation Ratio Models with Stata: Commands and OutputMaking Publication-Quality TablesPresenting the ResultsSummary of Stata Commands in this ChapterExercises7. Adjacent Categories Logistic Regression ModelsAdjacent Categories Models: An IntroductionResearch Example and Description of the Data and SampleAdjacent Categories Models with Stata: Commands and OutputPresenting the ResultsSummary of Stata Commands in this Chapter8. Stereotype Logistic Regression ModelsStereotype Logistic Regression Models: An IntroductionResearch Example and Description of Data and SampleStereotype Logistic Regression with Stata: Commands and OutputMaking Publication-Quality TablesPresenting the ResultsSummary of Stata Commands in this ChapterExercises9. Ordinal Logistic Regression with Complex Survey Sampling DesignsOrdinal Logistic Regression with Complex Survey Sampling Designs: An IntroductionResearch Example and the Description of Data and VariablesData Analysis with Stata: Commands and OutputMaking Publication-Quality TablesSummary of Stata Commands in this ChapterExercises10. Multilevel Modeling for Continuous and Binary Response VariablesMultilevel Modeling: An IntroductionMultilevel Modeling for Continuous Outcome VariablesMultilevel Modeling for Binary Outcome VariablesMultilevel Modeling for Binary Outcome Variables with Stata: Commands and OutputMaking Publication-Quality TablesReporting the Results11. Multilevel Modeling for Ordinal Response VariablesMultilevel Modeling for Ordinal Response Variables: An IntroductionResearch Example: Research Problem and QuestionsBuilding a Two-Level Model for Ordinal Response Variables with Stata: Commands and OutputMaking Publication-Quality TablesPresenting the ResultsSummary of Stata Commands in this ChapterExercises12. Beyond Ordinal Logistic Regression Models: Ordinal Probit Regression Models and Multinomial Logistic Regression ModelsOrdinal Probit ModelsMultinomial Logistic Regression ModelsSummary of Stata Commands in this ChapterExercises Review In this book, Xing Liu offers a well-crafted book focused on the application of ordinal response models across fields. Readers will be equipped to competently handle a variety of statistical techniques from basic correlations to more advanced generalized ordered logistic regression models. This is an excellent resource for both new consumers of these statistical applications to seasoned veterans working on more complex issues related to ordinal response models. -- Jennifer Hayes ClarkLogistic regression can be difficult to understand. Without a book explaining the test in a plain and easy-to-understand matter, learners will feel lost and get frustrated. However, Applied Ordinal Logistic Regression Using Stata explains the concept clearly and provides practical codes and output. Learners will find this book approachable and easy to follow. -- Lu Liu Review Quote Logistic regression can be difficult to understand. Without a book explaining the test in a plain and easy-to-understand matter, learners will feel lost and get frustrated. However, Applied Ordinal Logistic Regression Using Stataexplains the concept clearly and provides practical codes and output. Learners will find this book approachable and easy to follow. Details ISBN148331975X Author Xing Liu Short Title APPLIED ORDINAL LOGISTIC REGRE Language English ISBN-10 148331975X ISBN-13 9781483319759 Media Book Format Paperback Year 2015 Imprint SAGE Publications Inc Subtitle From Single-Level to Multilevel Modeling Place of Publication Thousand Oaks Country of Publication United States Birth 1958 Affiliation Eastern Connecticut State University Qualifications (Ed Pages 552 Publication Date 2015-12-16 UK Release Date 2015-12-16 NZ Release Date 2015-12-16 US Release Date 2015-12-16 Publisher SAGE Publications Inc DEWEY 001.422 Audience Tertiary & Higher Education AU Release Date 2015-12-15 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:136090780;
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ISBN-13: 9781483319759
Book Title: Applied Ordinal Logistic Regression Using Stata
Number of Pages: 552 Pages
Language: English
Publication Name: Applied Ordinal Logistic Regression Using Stata: from Single-Level to Multilevel Modeling
Publisher: Sage Publications Inc
Publication Year: 2015
Item Height: 231 mm
Item Weight: 810 g
Type: Textbook
Author: Xing Liu
Subject Area: Social Research
Item Width: 187 mm
Format: Paperback
