This is the third edition of this text on logistic regression methods, originally published in 1994, with its second e- tion published in 2002. As in the first two editions, each chapter contains a pres- tation of its topic in โlecture?bookโ format together with objectives, an outline, key formulae,
[Statistics for Biology and Health] Logistic Regression || Maximum Likelihood Techniques: An Overview
โ Scribed by Kleinbaum, David G.; Klein, Mitchel
- Book ID
- 118028522
- Publisher
- Springer New York
- Year
- 2010
- Tongue
- English
- Weight
- 644 KB
- Edition
- 3
- Category
- Article
- ISBN
- 144191742X
No coin nor oath required. For personal study only.
โฆ Synopsis
This is the third edition of this text on logistic regression methods, originally published in 1994, with its second e- tion published in 2002. As in the first two editions, each chapter contains a pres- tation of its topic in โlecture?bookโ format together with objectives, an outline, key formulae, practice exercises, and a test. The โlecture bookโ has a sequence of illust- tions, formulae, or summary statements in the left column of each page and a script (i. e. , text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This third edition has expanded the second edition by adding three new chapters and a modified computer appendix. We have also expanded our overview of mod- ing strategy guidelines in Chap. 6 to consider causal d- grams. The three new chapters are as follows: Chapter 8: Additional Modeling Strategy Issues Chapter 9: Assessing Goodness of Fit for Logistic Regression Chapter 10: Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves In adding these three chapters, we have moved Chaps. 8 through 13 from the second edition to follow the new chapters, so that these previous chapters have been ren- bered as Chaps. 11โ16 in this third edition.
๐ SIMILAR VOLUMES
This Book Presents Practical Approaches For The Analysis Of Data From Gene Expression Microarrays. Each Chapter Describes The Conceptual And Methodological Underpinning For A Statistical Tool And Its Implementation In Software. Methods Cover All Aspects Of Statistical Analysis Of Microarrays, From A