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Applied logistic regression analysis
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Applied logistic regression analysis

Author: Scott W Menard
Publisher: Thousand Oaks, Calif. : Sage Publications, ©2002.
Series: Sage university papers series., Quantitative applications in the social sciences ;, no. 07-106.
Edition/Format:   Book : English : 2nd edView all editions and formats
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Additional Physical Format: Online version:
Menard, Scott W.
Applied logistic regression analysis.
Thousand Oaks, Calif. : Sage Publications, c2002
(OCoLC)763149002
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Scott W Menard
ISBN: 0761922083 9780761922087
OCLC Number: 46729126
Description: viii, 111 p. : ill. ; 22 cm.
Contents: Linear Regression and the Logistic Regression Model --
Regression Assumptions --
Nonlinear Relationships and Variable Transformations --
Probabilities, Odds, Odds Ratios, and the Logit Transformation for Dichotomous Dependent Variables --
Logistic Regression: A First Look --
Summary Statistics for Evaluating the Logistic Regression Model --
R[superscript 2], F, and Sums of Squared Errors --
Goodness of Fit: G[subscript M], R[superscript 2 subscript L], and the Log Likelihood --
Predictive Efficiency: [lambda subscript p], [tau subscript p], [phi subscript p], and the Binomial Test --
Examples: Assessing the Adequacy of Logistic Regression Models --
Conclusion: Summary Measures for Evaluating the Logistic Regression Model --
Interpreting the Logistic Regression Coefficients --
Statistical Significance in Logistic Regression Analysis --
Interpreting Unstandardized Logistic Regression Coefficients --
Substantive Significance and Standardized Coefficients --
Exponentiated Coefficients or Odds Ratios --
More on Categorical Predictors: Contrasts and Interpretation --
Interaction Effects --
Stepwise Logistic Regression --
An Introduction to Logistic Regression Diagnostics --
Specification Error --
Collinearity --
Numerical Problems: Zero Cells and Complete Separation --
Analysis of Residuals --
Overdispersion and Underdispersion --
A Suggested Protocol for Logistic Regression Diagnostics --
Polytomous Logistic Regression and Alternatives to Logistic Regression --
Polytomous Nominal Dependent Variables.
Series Title: Sage university papers series., Quantitative applications in the social sciences ;, no. 07-106.
Responsibility: Scott Menard.
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