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Logistic Regression: A Self-Learning Text by Kleinbaum, David G|Klein, Mitchel

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ISBN
9780387953977
Subject Area
Mathematics, Medical, Social Science
Publication Name
Logistic Regression : a Self-Learning Text
Item Length
9.3 in
Publisher
Springer
Subject
Biostatistics, Probability & Statistics / Regression Analysis, Research, Statistics, Epidemiology
Publication Year
2005
Series
Statistics for Biology and Health Ser.
Type
Textbook
Format
Hardcover
Language
English
Author
David G. Kleinbaum, Mitchell Klein
Features
Revised
Item Width
8.1 in
Item Weight
42 Oz
Number of Pages
Xiv, 513 Pages

關於產品

Product Information

As in the first edition, each chapter contains a presentation of its topic in lecture-book format together with objectives, an outline, key formulae, practice exercises, and a test. The lecture-book has a sequence of illustrations and formulae in the left column of each page and a script in the right column. This format allows the script to be read in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented.

Product Identifiers

Publisher
Springer
ISBN-10
0387953973
ISBN-13
9780387953977
eBay Product ID (ePID)
2210316

Product Key Features

Author
David G. Kleinbaum, Mitchell Klein
Publication Name
Logistic Regression : a Self-Learning Text
Format
Hardcover
Language
English
Features
Revised
Subject
Biostatistics, Probability & Statistics / Regression Analysis, Research, Statistics, Epidemiology
Publication Year
2005
Series
Statistics for Biology and Health Ser.
Type
Textbook
Subject Area
Mathematics, Medical, Social Science
Number of Pages
Xiv, 513 Pages

Dimensions

Item Length
9.3 in
Item Width
8.1 in
Item Weight
42 Oz

Additional Product Features

Edition Number
2
LCCN
2002-019728
Lc Classification Number
R853.S7k54 2002
Edition Description
Revised Edition
Table of Content
Introduction to Logistic Regression * Important Special Cases of the Logistical Model * Computing the Odds Ration in Logistic Regression * Maximum Likelihood Techniques: An Overview * Statistical Inference Using Maximum Likelihood Techniques * Modeling Strategy Guidelines * Modeling Strategy for Assessing Interaction and Confounding * Analysis of Matched Data Using Logistic Regression * Polytomous Logistic Regression * Ordinal Logistic Regression * Logistic Regression for Correlated Data * GEE Examples * Other Approaches for Analysis of Correlated Data
Copyright Date
2005
Target Audience
College Audience
Dewey Decimal
610/.7/27
Dewey Edition
21
Illustrated
Yes

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