SPSS 13.0 Regression Models
Published on 23. August 2005
Book
Paperback/Softback
978-0-13-185724-7 (ISBN)
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 230 mm
Width: 189 mm
Thickness: 4 mm
Weight
127 gr
ISBN-13
978-0-13-185724-7 (9780131857247)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Content
1. Choosing a Procedure for Binary Logistic Regression Models
2. Logistic Regression
Logistic Regression Set Rule
Logistic Regression Variable Selection Methods
Logistic Regression Define Categorical Variables
Logistic Regression Save New Variables
Logistic Regression Options
LOGISTIC REGRESSION Command Additional Features
3. Multinomial Logistic Regression
Multinomial Logistic Regression Models
Multinomial Logistic Regression Reference Category
Multinomial Logistic Regression Statistics
Multinomial Logistic Regression Criteria
Multinomial Logistic Regression Options
Multinomial Logistic Regression Save
NOMREG Command Additional Features
4. Probit Analysis
Probit Analysis Define Range
Probit Analysis Options
PROBIT Command Additional Features
5. Nonlinear Regression
Conditional Logic (Nonlinear Regression)
Nonlinear Regression Parameters
Nonlinear Regression Common Models
Nonlinear Regression Loss Function
Nonlinear Regression Parameter Constraints
Nonlinear Regression Save New Variables
Nonlinear Regression Options
Interpreting Nonlinear Regression Results
NLR Command Additional Features
6. Weight Estimation
Weight Estimation Options
WLS Command Additional Features
7. Two-Stage Least-Squares Regression
Two-Stage Least-Squares Regression Options
2SLS Command Additional Features
Appendix
A. Categorical Variable Coding Schemes
Deviation
Simple
Helmert
Difference
Polynomial
Repeated
Special
Indicator
Index
2. Logistic Regression
Logistic Regression Set Rule
Logistic Regression Variable Selection Methods
Logistic Regression Define Categorical Variables
Logistic Regression Save New Variables
Logistic Regression Options
LOGISTIC REGRESSION Command Additional Features
3. Multinomial Logistic Regression
Multinomial Logistic Regression Models
Multinomial Logistic Regression Reference Category
Multinomial Logistic Regression Statistics
Multinomial Logistic Regression Criteria
Multinomial Logistic Regression Options
Multinomial Logistic Regression Save
NOMREG Command Additional Features
4. Probit Analysis
Probit Analysis Define Range
Probit Analysis Options
PROBIT Command Additional Features
5. Nonlinear Regression
Conditional Logic (Nonlinear Regression)
Nonlinear Regression Parameters
Nonlinear Regression Common Models
Nonlinear Regression Loss Function
Nonlinear Regression Parameter Constraints
Nonlinear Regression Save New Variables
Nonlinear Regression Options
Interpreting Nonlinear Regression Results
NLR Command Additional Features
6. Weight Estimation
Weight Estimation Options
WLS Command Additional Features
7. Two-Stage Least-Squares Regression
Two-Stage Least-Squares Regression Options
2SLS Command Additional Features
Appendix
A. Categorical Variable Coding Schemes
Deviation
Simple
Helmert
Difference
Polynomial
Repeated
Special
Indicator
Index