Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered. : Logistic Regression Models (Chapman & Hall/CRC Texts in Statistical Science) (): Joseph M. Hilbe: Books. Logistic Regression Models. Joseph M Hilbe. ERRATA and COMMENTS. 4 th. Printing (Printed Sept, ). (updated to: 12 December, ).
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All instructor resources are now available on our Instructor Hub. The student resources previously accessed via GarlandScience. What are VitalSource eBooks? For Instructors Request Inspection Copy. Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical hillbe regression procedures.
Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models to health, environmental, physical, and social modelss data.
“Logistic Regression Using R” by Joseph Hilbe
Examples illustrate successful modeling The text first provides basic terminology and concepts, before explaining the foremost methods of estimation maximum likelihood and IRLS appropriate for logistic models.
It then presents an in-depth discussion of related terminology and examines logistic regression model development and interpretation of the results. After focusing on the construction and interpretation of various interactions, the author evaluates assumptions and goodness-of-fit tests that hilbee be used for model assessment. He also covers binomial logistic regression, varieties of overdispersion, and regressoon number of extensions to the basic binary and binomial logistic model.
Both real and simulated data are used to explain and test the concepts involved. The appendices give an overview of marginal effects and discrete change as well as a page tutorial on using Stata commands related to the examples used in the text. Stata is used for most examples while R is provided at the end of the chapters to replicate examples in the text.
Logistic Regression Models
Derivation of the Beta-Binomial Appendix F: Data Sets Appendix H: Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods.
Readers familiar with his other expository work will know what to expect—great clarity.
The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip “obvious” sections.
The material has been thoroughly road-tested through classroom and web-based teaching. The audience is not just students meeting the topic for the first time, but also experienced users.
Dobson, BiometricsJune Overall this is a comprehensive book, which will provide a very useful resource and handbook for anyone whose work involves modelling binary data.
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Summary Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Loyistic Professor Hilbe discuss the book. Dobson, Biometrics modele, June Overall this is a comprehensive book, which will provide a very useful resource and handbook for anyone whose work involves modelling binary data. Hand, International Statistical Review79 … useful as a textbook in a course on logistic regression.
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