Elementary regression modeling : a discrete approach /: a discrete approach. (2016)

• Record Type: Book
• Further Information: Note: Roger A. Wojtkiewicz, Ball State University.
• Authors: Wojtkiewicz, Roger A
• Contents: Chapter 1: Introductory Ideas; Regression Modeling; Control Modeling; Modeling Interactions; Modeling Linearity With Splines; Testing Research Hypotheses; Classical Approach to Regression; Disadvantages of Classical Approach; Discrete Approach to Regression; Summary; Key Concepts; Notes; Chapter 2: Basic Statistical Procedures; Individual Units and Groups; Measurement; Level of Measurement; Examples for Level of Measurement; Count, Sum, and Transformations; Mean; Proportion and Percentage; Odds and Log odds; Examples of Means and Log Odds; Differences; Summary; Key Concepts; Chapter Exercises; Notes; Chapter 3: Regression Modeling Basics; Difference between Means: The t-test; Linear Regression With a Two-Category Independent Variable; Logistic Regression With a Two-Category Independent Variable; Linear Regression With a Four-Category Independent Variable; Logistic Regression With a Four-Category Independent Variable; Modeling Linear Effect With Dummy Variables; Linear Coefficient in Linear Regression; Linear Coefficient in Logistic Regression; Using Dummy Variables for a Continuous Variable; Summary; Key Concepts; Chapter Exercises; Notes; Chapter 4: Key Regression Modeling Concepts; Unit Vector: Estimating the Intercept; Nestedness; Higher-Order Differences; Constraints; Summary; Key Concepts<br />Chapter Exercises; Notes; Chapter 5: Control Modeling; Elementary Control Modeling; Elaboration for Controlling; Demographic Standardization for Controlling; Small and Big Models; Allocating Influence With Multiple Control Variables; One-at-a-Time Without Controls; Step Approach; One-at-a-Time With Controls; Hybrid Approach; Nestedness and Constraints; Example Using Logistic Regression; Summary; Key Concepts; Chapter Exercises; Notes; Chapter 6: Modeling Interactions; Interactions as Conditional Differences; Interactions Between Dummy Variables; Interactions Between Dummy Variables and an Interval Variable; Three-Way Interactions; Estimating Separate Models; Example Using Logistic Regression; Summary; Key Concepts; Chapter Exercises; Notes; Chapter 7: Modeling Linearity With Splines; Dummy Variables Nested in an Interval Variable; Introduction to Knotted Spline Variables; Spline Variables Nested in an Interval Variable; Regression Modeling Using Spline Variables; Working With a Continuous Independent Variable; Example Using Logistic Regression; Summary; Key Concepts; Chapter Exercises; Notes; Chapter 8: Conclusion: Testing Research Hypotheses; Bivariate Hypothesis/No Controls; Bivariate Hypothesis/Unanalyzed Controls; Bivariate Hypothesis/Analyzed Controls; Hypothesis Involving Interactions; Hypothesis Involving Nonlinearity; Final Comments; Key Concepts; Summary; Chapter exercises; Notes;
• Publisher Details: Thousand Oaks : SAGE Publications, Inc
• Publication Date: 2016
• Extent: 1 online resource (240 pages)
• Subjects: 300.1/519536; Social sciences -- Statistical methods; Regression analysis
• Languages: English
• ISBNs: 9781506303499; 1506303498
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.