Modern Methods for Robust Regression (Quantitative Applications in the Social Sciences) - Softcover

9781412940726: Modern Methods for Robust Regression (Quantitative Applications in the Social Sciences)
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Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, geared toward both future and practicing social scientists, is unique in that it takes an applied approach and offers readers empirical examples to illustrate key concepts. It is ideal for readers who are interested in the issues related to outliers and influential cases.

Key Features

  • Defines key terms necessary to understanding the robustness of an estimator: Because they form the basis of robust regression techniques, the book also deals with various measures of location and scale.
  • Addresses the robustness of validity and efficiency: After having described the robustness of validity for an estimator, the author discusses its efficiency.
  • Focuses on the impact of outliers: The book compares the robustness of a wide variety of estimators that attempt to limit the influence of unusual observations.
  • Gives an overview of some traditional techniques: Both formal statistical tests and graphical methods detect influential cases in the general linear model.
  • Offers a Web appendix: This volume provides readers with the data and the R code for the examples used in the book.

Intended Audience

This is an excellent text for intermediate and advanced Quantitative Methods and Statistics courses offered at the graduate level across the social sciences.

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About the Author:
Robert Andersen is a Professor of Sociology and Political Science at the University of Toronto. His research interests are in applied statistics, political sociology (especially the social bases of attitudes and political behavior), social stratification, and the sociology of work. Some of his recent work has appeared in the American Sociological Review, the Journal of Politics, and Sociological Methodology.

"About this title" may belong to another edition of this title.

  • PublisherSAGE Publications, Inc
  • Publication date2007
  • ISBN 10 1412940729
  • ISBN 13 9781412940726
  • BindingPaperback
  • Edition number1
  • Number of pages128

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Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, geared toward both future and practicing social scientists, is unique in that it takes an applied approach and offers readers empirical examples to illustrate key concepts. It is ideal for readers who are interested in the issues related to outliers and influential cases.Key FeaturesDefines key terms necessary to understanding the robustness of an estimator: Because they form the basis of robust regression techniques, the book also deals with various measures of location and scale.Addresses the robustness of validity and efficiency: After having described the robustness of validity for an estimator, the author discusses its efficiency.Focuses on the impact of outliers: The book compares the robustness of a wide variety of estimators that attempt to limit the influence of unusual observations.Gives an overview of some traditional techniques: Both formal statistical tests and graphical methods detect influential cases in the general linear model.Offers a Web appendix: This volume provides readers with the data and the R code for the examples used in the book.Intended AudienceThis is an excellent text for intermediate and advanced Quantitative Methods and Statistics courses offered at the graduate level across the social sciences.Learn more about 'The Little Green Book' - QASS Series! Click Here. Seller Inventory # 9781412940726

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