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
Applied Logistic Regression (Hosmer/Applied Logistic Regression) || Front Matter
โ Scribed by Hosmer, David W.; Lemeshow, Stanley
- Book ID
- 120473167
- Publisher
- John Wiley & Sons, Inc.
- Year
- 2005
- Tongue
- English
- Weight
- 312 KB
- Edition
- 2nd
- Category
- Article
- ISBN
- 0471356328
No coin nor oath required. For personal study only.
โฆ Synopsis
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. 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. David W. Hosmer, Stanley Lemeshow. A Wiley-interscience Publication. Includes Bibliographical References (p. 352-365) And Index.
๐ SIMILAR VOLUMES
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