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Applied logistic regression / David W. Hosmer, Stanley Lemeshow.

Κατά: Συντελεστής(ές): Τύπος υλικού: ΚείμενοΚείμενοΣειρά: Wiley series in probability and statistics. Texts and references sectionΛεπτομέρειες δημοσίευσης: New York : Wiley, c2000.Έκδοση: 2η έκδΠεριγραφή: 1 ηλεκτρονική πηγή (xii, 375 σ.) : εικISBN:
  • 0471654027
  • 9780471654025
  • 9780471722144
  • 0471722146
  • 0471673803
  • 9780471673804
Θέμα(τα): Είδος/Μορφή: Ταξινόμηση DDC:
  • 519.5/36 22
NLM classification:
  • QA 37
Πηγές στο διαδίκτυο:
Περιεχόμενα:
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.
Περίληψη: In this revised and updated edition, the authors continue to provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. They extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by real-world examples-with extensive data sets available over the Internet.
Δεν αντιστοιχούν φυσικά τεκμήρια σε αυτήν την εγγραφή

"A Wiley-Interscience publication."

Includes bibliographical references (pages 354-367) and index.

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.

In this revised and updated edition, the authors continue to provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. They extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by real-world examples-with extensive data sets available over the Internet.

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