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Logistic Regression: From Introductory to Advanced Concepts and Applications
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- Book Title
- Logistic Regression: From Introductory to Advanced Concepts and A
- Publication Date
- 2009-04-01
- Pages
- 392
- ISBN
- 9781412974837
- Subject Area
- Technology & Engineering, Social Science
- Publication Name
- Logistic Regression : from Introductory to Advanced concepts and Applications
- Publisher
- SAGE Publications, Incorporated
- Item Length
- 9.7 in
- Subject
- Military Science, Research
- Publication Year
- 2009
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1.1 in
- Item Weight
- 28 Oz
- Item Width
- 7.7 in
- Number of Pages
- 392 Pages
關於產品
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
1412974836
ISBN-13
9781412974837
eBay Product ID (ePID)
109197401
Product Key Features
Number of Pages
392 Pages
Publication Name
Logistic Regression : from Introductory to Advanced concepts and Applications
Language
English
Publication Year
2009
Subject
Military Science, Research
Type
Textbook
Subject Area
Technology & Engineering, Social Science
Format
Hardcover
Dimensions
Item Height
1.1 in
Item Weight
28 Oz
Item Length
9.7 in
Item Width
7.7 in
Additional Product Features
Intended Audience
College Audience
LCCN
2008-049935
Illustrated
Yes
Table Of Content
PrefaceChapter 1. Introduction: Linear Regression and Logistic RegressionChapter 2. Log-Linear Analysis, Logit Analysis, and Logistic RegressionChapter 3. Quantitative Approaches to Model Fit and Explained VariationChapter 4. Prediction Tables and Qualitative Approaches to Explained VariationChapter 5. Logistic Regression CoefficientsChapter 6. Model Specification, Variable Selection, and Model BuildingChapter 7. Logistic Regression Diagnostics and Problems of InferenceChapter 8. Path Analysis With Logistic Regression (PALR)Chapter 9. Polytomous Logistic Regression for Unordered Categorical VariablesChapter 10. Ordinal Logistic RegressionChapter 11. Clusters, Contexts, and Dependent Data: Logistic Regression for Clustered Sample Survey DataChapter 12. Conditional Logistic Regression Models for Related SamplesChapter 13. Longitudinal Panel Analysis With Logistic RegressionChapter 14. Logistic Regression for Historical and Developmental Change Models: Multilevel Logistic Regression and Discrete Time Event History AnalysisChapter 15. Comparisons: Logistic Regression and Alternative ModelsAppendix A: ESTIMATION FOR LOGISTIC REGRESSION MODELSAppendix B: PROOFS RELATED TO INDICES OF PREDICTIVE EFFICIENCYAppendix C: ORDINAL MEASURES OF EXPLAINED VARIATIONReferencesIndex
Synopsis
In this text, author Scott Menard provides coverage of not only the basic logistic regression model but also advanced topics found in no other logistic regression text. The book keeps mathematical notation to a minimum, making it accessible to those with more limited statistics backgrounds, while including advanced topics of interest to more statistically sophisticated readers. Not dependent on any one software package, the book discusses limitations to existing software packages and ways to overcome them. Key Features Examines the logistic regression model in detail Illustrates concepts with applied examples to help readers understand how concepts are translated into the logistic regression model Helps readers make decisions about the criteria for evaluating logistic regression models through detailed coverage of how to assess overall models and individual predictors for categorical dependent variables Offers unique coverage of path analysis with logistic regression that shows readers how to examine both direct and indirect effects using logistic regression analysis Applies logistic regression analysis to longitudinal panel data, helping students understand the issues in measuring change with dichotomous, nominal, and ordinal dependent variables Shows readers how multilevel change models with logistic regression are different from multilevel growth curve models for continuous interval or ratio-scaled dependent variables Logistic Regression is intended for courses such as Regression and Correlation, Intermediate/Advanced Statistics, and Quantitative Methods taught in departments throughout the behavioral, health, mathematical, and social sciences, including applied mathematics/statistics, biostatistics, criminology/criminal justice, education, political science, public health/epidemiology, psychology, and sociology., The well-established gold standard in texts on collection development, Collection Management Basics: Sixth Edition provides a new edition to the last Developing Library and Information Center Collections book providing a completely fresh approach to the material. This latest edition continues to cover all aspects of collection development and management, including subjects such as needs assessment, policies, selection process theory and practice, protection, legal issues, censorship, and intellectual freedom. The book represents a total restructuring of the previous work, and reflects changes brought on by new technology and the up-and-down economy. Students and practitioners alike will benefit greatly from this up-to-date and essential text., Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.
LC Classification Number
HA31.3.M46 2010
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