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Angewandte ordinale logistische Regression unter Verwendung von Statistiken: von einstufig zu mehrstufig-

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Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel
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Book Title
Applied Ordinal Logistic Regression Using Stata: From Single-Leve
Publication Date
2015-11-11
Pages
552
ISBN
9781483319759
Publication Year
2015
Type
Textbook
Format
Trade Paperback
Language
English
Publication Name
Applied Ordinal Logistic Regression Using Stata : from Single-Level to Multilevel Modeling
Item Height
0.7in
Author
Xing Liu
Item Length
9.1in
Publisher
SAGE Publications, Incorporated
Item Width
7.4in
Item Weight
28.6 Oz
Number of Pages
552 Pages

Über dieses Produkt

Product Information

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.

Product Identifiers

Publisher
SAGE Publications, Incorporated
ISBN-10
148331975x
ISBN-13
9781483319759
eBay Product ID (ePID)
23038777136

Product Key Features

Author
Xing Liu
Publication Name
Applied Ordinal Logistic Regression Using Stata : from Single-Level to Multilevel Modeling
Format
Trade Paperback
Language
English
Publication Year
2015
Type
Textbook
Number of Pages
552 Pages

Dimensions

Item Length
9.1in
Item Height
0.7in
Item Width
7.4in
Item Weight
28.6 Oz

Additional Product Features

Lc Classification Number
Qa278.2.L585 2016
Reviews
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., 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. , 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 Stata explains the concept clearly and provides practical codes and output.  Learners will find this book approachable and easy to follow. 
Table of Content
1. Stata Basics Introduction to Stata Data Management Graphs A Summary of Stata Commands in this Chapter Exercises2. Review of Basic Statistics Understand Your Data Using Descriptive Statistics Descriptive Statistics for Continuous Variables Using Stata Frequency Distribution for Categorical Variables Using Stata Independent Samples t-test Using Stata Paired Samples t-test Analysis of Variance (ANOVA) Correlation Simple Linear Regression Multiple Linear Regression Chi-Square Test Making Publication-Quality Tables Using Stata General Guidelines for Reporting Resutls A Summary of Stata Commands in this Chapter Exercises3. Logistic Regression for Binary Data Logistic Regression Models: An Introduction Research Example and Description of the Data and Sample Logistic Regression with Stata: Commands and Output Summary of Stata Commands in this Chapter Exercises4. Proportional Odds Models for Ordinal Response Variables Proportional Odds Models: An Introduction Research Example and Description of the Data and Sample Proportional Odds Models with Stata: Commands and Output Summary of Stata Commands in this Chapter Exercises5. Partial Proportional Odds Models and Generalized Ordinal Logistic Regression Models Introduction Research Example and Description of the Data and Sample Partial Proportional Odds Models with Stata: Commands and Output Generalized Ordinal Logistic Regression Models with Stata: An Example Making Publication-Quality Tables Presenting the Results Summary of Stata Commands in this Chapter Exercises6. Continuation Ratio Models Continuation Ratio Models: An Introduction Research Example and Description of the Data and Sample Continuation Ratio Models with Stata: Commands and Output Making Publication-Quality Tables Presenting the Results Summary of Stata Commands in this Chapter Exercises7. Adjacent Categories Logistic Regression Models Adjacent Categories Models: An Introduction Research Example and Description of the Data and Sample Adjacent Categories Models with Stata: Commands and Output Presenting the Results Summary of Stata Commands in this Chapter8. Stereotype Logistic Regression Models Stereotype Logistic Regression Models: An Introduction Research Example and Description of Data and Sample Stereotype Logistic Regression with Stata: Commands and Output Making Publication-Quality Tables Presenting the Results Summary of Stata Commands in this Chapter Exercises9. Ordinal Logistic Regression with Complex Survey Sampling Designs Ordinal Logistic Regression with Complex Survey Sampling Designs: An Introduction Research Example and the Description of Data and Variables Data Analysis with Stata: Commands and Output Making Publication-Quality Tables Summary of Stata Commands in this Chapter Exercises10. Multilevel Modeling for Continuous and Binary Response Variables Multilevel Modeling: An Introduction Multilevel Modeling for Continuous Outcome Variables Multilevel Modeling for Binary Outcome Variables Multilevel Modeling for Binary Outcome Variables with Stata: Commands and Output Making Publication-Quality Tables Reporting the Results11. Multilevel Modeling for Ordinal Response Variables Multilevel Modeling for Ordinal Response Variables: An Introduction Research Example: Research Problem and Questions Building a Two-Level Model for Ordinal Response Variables with Stata: Commands and Output Making Publication-Quality Tables Presenting the Results Summary of Stata Commands in this Chapter Exercises12. Beyond Ordinal Logistic Regression Models: Ordinal Probit Regression Models and Multinomial Logistic Regression Models Ordinal Probit Models Multinomial Logistic Regression Models Summary of Stata Commands in this Chapter Exercises
Copyright Date
2016
Topic
Probability & Statistics / Regression Analysis, Research, Statistics
Lccn
2015-023615
Dewey Decimal
519.5/35
Intended Audience
College Audience
Dewey Edition
23
Genre
Mathematics, Social Science

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