David W. Hosmer, Stanley Lemeshow

Applied Logistic Regression

• Gebundenes Buch

Produktbeschreibung

Die logistische Regression (LR) gehört seit den 60er Jahren zu den Standardmethoden der Datenanalyse, besonders im Bereich der Medizin. Dieser neu aufgelegte, dabei sorgfältig überarbeitete Band spiegelt die wichtigsten inhaltlichen und technischen Entwicklungen der letzten beiden Jahrzehnte auf diesem Gebiet wieder. Der in mittlerem Schwierigkeitsgrad gehaltene Text eignet sich für Studenten und Praktiker aus der Biostatistik und der Epidemiologie.

Produktdetails

• Verlag: Wiley & Sons
• 2nd ed.
• Seitenzahl: 328
• Englisch
• Abmessung: 24mm x 20mm
• Gewicht: 670g
• ISBN-13: 9780471356325
• ISBN-10: 0471356328
• Artikelnr.: 09372657

Autorenporträt

DAVID W. HOSMER, PhD, is Professor of Biostatistics at the School of Public Health and Health Sciences at the University of Massachusetts at Amherst.

STANLEY LEMESHOW, PhD, is Professor of Biostatistics and Director of the Biostatistics Program at The Ohio State University.

Inhaltsangabe

From the contents:
Introduction to the Logistic Regression Model.

Multiple Logistic Regression.

Interpretation of the Fitted Logistic Regression Model.

Model-Building Strategies and Methods for Logistic Regression.

Assessing the Fit of the Model.

Application of Logistic Regression with Different Sampling Models.

Logistic Regression for Matched Case-Control Studies.

Special Topics.

References.

Index.

Rezensionen

"...the revised text continues to provide a focused introduction to the logistic regression model and its use in methods for modelling..." (Short Book Reviews, Vol. 21, No. 2, August 2001)

"In this revised and updated edition of the popular test, the authors incorporate theoretical and computing advances from the last decade." (Journal of the American Statistical Association, September 2001)

"...an excellent book that balances many objectives well.... All statistical practitioners...can benefit from this book...Applied Logistic Regression is an ideal choice." (Technometrics, February 2002)

"...a focused introduction to the logistic regression model and its use in methods for modeling the relationship between a categorical outcome variable and a set of covariates." (Zentralblatt MATH, Vol. 967, 2001/17)