Hilbe Modeling Count Data

Erscheinungsjahr 2014
ISBN: 978-1-139-98997-8
Verlag: Cambridge University Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 0 Seiten

This entry-level text offers clear and concise guidelines on how to select, construct, interpret and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of linear regression and works up to an analysis of the Poisson and negative binomial models, and to the problem of overdispersion. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in public health, ecology, econometrics, transportation, and other related fields.

Autoren/Hrsg.

Hilbe, Joseph M.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie

Inhaltsverzeichnis

Preface; 1. Varieties of count data; 2. Poisson regression; 3. Testing overdispersion; 4. Assessment of fit; 5. Negative binomial regression; 6. Poisson inverse Gaussian regression; 7. Problems with zeros; 8. Modeling under-dispersed count data – generalized Poisson; 9. Complex data: more advanced models; Appendix A: SAS code; References; Index.

Über Autor(innen)

Hilbe, Joseph M.
Joseph Hilbe is a solar system ambassador with NASA's Jet Propulsion Laboratory, California Institute of Technology; an Adjunct Professor of Statistics at Arizona State University; an Emeritus Professor at the University of Hawaii; and a statistical modeling instructor for Statistics.com, a web-based continuing-education program in statistics. He is the author of several books on statistical modeling and serves as the coordinating editor for the Cambridge University Press series Predictive Analytics in Action.