Quantile regression /
In Quantile Regression, authors Lingxin Hao and Daniel Q. Naiman establish the seldom-recognized link between inequality studies and quantile regression models. Using remarkably clear statistical explanations and. exceptionally rich empirical examples, the authors uniquely create a bridge between th...
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| Format: | Book |
| Language: | English |
| Published: |
Thousand Oaks, Calif. :
Sage Publications,
[2007], ©2007
Thousand Oaks, Calif. : c2007 Thousand Oaks, Calif. : ©2007 Thousand Oaks, Calif. : [2007] |
| Series: | Quantitative applications in the social sciences ;
no. 07-149 Quantitative applications in the social sciences no. 07-149. |
| Subjects: | |
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| Summary: | In Quantile Regression, authors Lingxin Hao and Daniel Q. Naiman establish the seldom-recognized link between inequality studies and quantile regression models. Using remarkably clear statistical explanations and. exceptionally rich empirical examples, the authors uniquely create a bridge between the new and conventional modeling frameworks "In Quantile Regression, authors Lingxin Hao and Daniel Q. Naiman establish the seldom-recognized link between inequality studies and quantile regression models. Using clear statistical explanations and empirical examples, the authors create a bridge between the new and conventional modeling frameworks. This book is intended for courses dedicated to regression, as well as graduate-level, intermediate, and advanced quantitative methods and statistics courses across the social sciences."--BOOK JACKET Key Features: Establishes a natural link between quantile regression and inequality studies: Though separate methodological literatures exists for each subject matter, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Develops conditional shape-shift measures based on quantile regression estimates: These measures provide direct solutions to research questions about a covariate's impact on the shape of the response distribution. Presents straightforward methods: The authors use clear explanations to obtain a covariate's effect on the location and shape of conditional quantile functions in absolute terms from fitted models on the log-scale. Incorporates language and procedures common among social scientists: The authors offer clearly defined terms, simplified equations, illustrative graphs, tables and graphs based on empirical data, and computational codes using statistical software |
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| Physical Description: | ix, 126 p. : ill ; 22 cm ix, 126 p. : ill. ; 22 cm ix, 126 pages : illustrations ; 22 cm |
| Bibliography: | Includes bibliographical references (p. 121-122) and index Includes bibliographical references (pages 121-122) and index |
| ISBN: | 1412926289 (pbk. : alk. paper) 1412926289 (pbk.) 1412926289 1412985552 9781412926287 (pbk. : alk. paper) 9781412926287 (pbk.) 9781412926287 9781412985550 |