Quantile Regression

· SAGE Publications
Libro electrónico
136
Páginas
Apto
Las calificaciones y opiniones no están verificadas. Más información

Acerca de este libro electrónico

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
  • Acerca del 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.

    Califica este libro electrónico

    Cuéntanos lo que piensas.

    Información de lectura

    Smartphones y tablets
    Instala la app de Google Play Libros para Android y iPad/iPhone. Como se sincroniza de manera automática con tu cuenta, te permite leer en línea o sin conexión en cualquier lugar.
    Laptops y computadoras
    Para escuchar audiolibros adquiridos en Google Play, usa el navegador web de tu computadora.
    Lectores electrónicos y otros dispositivos
    Para leer en dispositivos de tinta electrónica, como los lectores de libros electrónicos Kobo, deberás descargar un archivo y transferirlo a tu dispositivo. Sigue las instrucciones detalladas que aparecen en el Centro de ayuda para transferir los archivos a lectores de libros electrónicos compatibles.