You are here

Quantile Regression

Quantile Regression

April 2007 | 136 pages | SAGE Publications, Inc
Quantile Regression establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literatures exist for each subject matter, the authors explore the natural connections between this increasingly sought-after tool and research topics in the social sciences.
Series Editor's Introduction
1. Introduction
2. Quantiles and Quantile Functions
3. Quantile-Regression Model and Estimation
4. Quantile Regression Inference
5. Interpretation of Quantile-Regression Estimates
6. Interpretation of Monotone-Transformed QRM
7. Application to Income Inequality in 1991 and 2001
Appendix: Stata Codes
About the Authors

Lingxin Hao

Lingxin Hao is a professor of sociology at Johns Hopkins University. Her specialties include quantitative methodology, social inequality, sociology of education, migration, and family and public policy. She is the lead author of two QASS monographs Quantile Regression and Assessing Inequality. Her research has appeared in the Sociological Methodology, Sociological Methods and Research, American Journal of Sociology, Demography, Social Forces, Sociology of Education, and Child Development, among others. More About Author

Daniel Q. Naiman

Daniel Q. Naiman (PhD, Mathematics, 1982, University of Illinois at Urbana-Champaign) is Professor and Chair of the Applied Mathematics and Statistics at the Johns Hopkins University. He was elected as a Fellow of the Institute of Mathematical Statistics in 1997, and was an Erskine Fellow at the University of Canterbury in 2005. Much of his mathematical research has been focused on geometric and computational methods for multiple testing. He has collaborated on papers applying statistics in a variety of areas: bioinformatics, econometrics, environmental health, genetics, hydrology, and microbiology. His articles have appeared in various... More About Author

For instructors

To inquire about the availability of this title for review (print and/or digital), please contact your local sales representative or call (800) 818-7243.

Purchasing options

Please select a format:

ISBN: 9781412926287

SAGE Knowledge is the ultimate social sciences digital library for students, researchers, and faculty. Hosting more than 4,400 titles, it includes an expansive range of SAGE eBook and eReference content, including scholarly monographs, reference works, handbooks, series, professional development titles, and more.

The platform allows researchers to cross-search and seamlessly access a wide breadth of must-have SAGE book and reference content from one source.