Quantile Regression

Lingxin Hao · Daniel Q. Naiman

apr. 2007 · SAGE Publications

Carte electronică

136

Pagini

Eligibilă

Evaluările și recenziile nu sunt verificate Află mai multe

Despre această carte electronică

Quantile Regression, the first book of Hao and Naiman′s two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines.

Key Features:

Establishes a natural link between quantile regression and inequality studies in the social sciences

Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples

Includes computational codes using statistical software popular among social scientists

Oriented to empirical research

Despre autor

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.

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 journals including Annals of Statistics, Bioinformatics, Biometrika, Human Heredity, Journal of Multivariate Analysis, Journal of the American Statistical Association, and Science.

Evaluează cartea electronică

Spune-ne ce crezi.

Informații despre lectură

Smartphone-uri și tablete

Instalează aplicația Cărți Google Play pentru Android și iPad/iPhone. Se sincronizează automat cu contul tău și poți să citești online sau offline de oriunde te afli.

Laptopuri și computere

Poți să asculți cărțile audio achiziționate pe Google Play folosind browserul web al computerului.

Dispozitive eReader și alte dispozitive

Ca să citești pe dispozitive pentru citit cărți electronice, cum ar fi eReaderul Kobo, trebuie să descarci un fișier și să îl transferi pe dispozitiv. Urmează instrucțiunile detaliate din Centrul de ajutor pentru a transfera fișiere pe dispozitivele eReader compatibile.

Raportează conținut ilegal