UID:
almafu_9961900683602883
Umfang:
1 online resource (xv, 107 p.) :
,
ill.
ISBN:
9781412985109 (ebook) :
,
9781544332567
,
1544332564
,
9781452213200
,
1452213208
,
9781412985109
,
1412985102
Serie:
Quantitative applications in the social sciences ; no. 07-152
Inhalt:
Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.
Anmerkung:
Bibliographic Level Mode of Issuance: Monograph
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Cover page -- Title -- Copyright -- Contents -- List of Figures -- List of Tables -- Series Editor's Introduction -- Acknowledgments -- 1. Introduction -- Defining Robustness -- Defining Robust Regression -- A Real-World Example: Coital Frequency of Married Couples in the 1970s -- 2. Important Background -- Bias and Consistency -- Breakdown Point -- Influence Function -- Relative Efficiency -- Measures of Location -- The Mean -- α-Trimmed Mean -- The Median -- Measures of Scale -- Standard Deviation -- Mean Deviation From the Mean -- Mean Deviation From the Median -- Interquartile Range -- Median Absolute Deviation -- M-Estimation -- M-Estimation of Location -- Huber Estimates -- Biweight Estimates -- M-Estimators of Scale -- Comparing Various Estimates -- EXAMPLE 2.1: Simulated Data -- EXAMPLE 2.2: Public Opinion Toward Pay Inequality in Cross-National Perspective -- Notes -- 3. Robustness, Resistance, and Ordinary Least Squares Regression -- Ordinary Least Squares Regression -- Implications of Unusual Cases for OLS Estimates and Standard Errors -- EXAMPLE 3.1: Income Inequality and Public Opinion Toward Pay Equality in 26 New Democracies -- Detecting Problematic Observations in OLS Regression -- Detecting Leverage: Hat Values -- Detecting Regression Outliers: Studentized Residuals and the Bonferroni Adjustment -- Detecting Influence: DFBETAs, Cook's D, and Partial Regression Plots -- Some Strategies for Dealing With Influential Cases -- Notes -- 4. Robust Regression for the Linear Model -- L-Estimators -- Least Absolute Values Regression -- Least Median of Squares Regression -- Least Trimmed Squares Regression -- R-Estimators -- M-Estimators -- Iteratively Reweighted Least Squares -- GM-Estimators -- S-Estimators -- Generalized S-Estimators -- MM-Estimators -- Comparing the Various Estimators -- EXAMPLE 4.1: Simulated Data.
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EXAMPLE 4.2: Multiple Regression Predicting Public Opinion -- Diagnostics Revisited: Robust Regression-Related Methods for Detecting Outliers -- Index Plots of the Weights From the Final IWLS Fit -- RR-Plots (''Residual-Residual'' Plots) -- Robust Distances -- Notes -- 5. Standard Errors for Robust Regression -- Asymptotic Standard Errors for Robust Regression Estimators -- Bootstrapped Standard Errors -- Random-x Bootstrapping -- Fixed-x Bootstrapping -- Constructing Confidence Intervals -- EXAMPLE 5.1: The Impact of Democracy on the Effects of Income Inequality and Per Capita GDP on Public Opinion -- Notes -- 6. Influential Cases in Generalized Linear Models -- The Generalized Linear Model -- Detecting Unusual Cases in Generalized Linear Models -- Residuals From the GLM -- Hat Values and Leverage -- Assessing Influence -- Robust Generalized Linear Models -- M-Estimation for GLMs -- EXAMPLE 6.1: Logistic Regression Predicting Vote for the Labour Party in Britain, 2001 -- EXAMPLE 6.2: Robust Poisson Regression Predicting Voluntary Association Membership in Quebec -- Notes -- 7. Conclusions -- Appendix: Software Considerations for Robust Regression -- References -- Index -- About the Author.
,
English
Weitere Ausg.:
ISBN 9781412940726
Weitere Ausg.:
ISBN 1412940729
Sprache:
Englisch
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