4 internautes sur 4 ont trouvé ce commentaire utile
Sitting in Seattle
- Publié sur Amazon.com
If you want to learn about logistic regression (LR), and are an applied statistics user (especially in medical, health, or policy areas), this is the book for you. It is thorough in coverage and focuses deeply on the fundamentals: understanding applications of LR, interpreting the results, developing intuition for the procedures, and avoiding common errors.
You might wonder: what is LR good for? The answer: when you want to assess a dichotomous outcome on the basis of any kind of predictors. For example, to predict disease occurrence (0/1) on the basis of gender, behaviors, income, etc. Or to predict a behavior (0/1) on the basis of psychological scores, demographics, etc.
The book follows a "lecture plus commentary" style, where a primary didactic text is heavily annotated with sidebar comments, summaries, reviews of the material, and quizzes with answers. Overall this is a good thing and makes the book extremely well-suited for self study. However, it also makes it extremely long and moderately tedious to read at times. Unlike many stats books, however, it actually is readable.
The mathematics are held to a high school level (i.e., algebra), so it is suitable for any applied researcher or research consumer, although therefore probably not suitable for a professional statistician. Still, it is mathematically rigorous and requires to reader to work through a large number of (simple) formulas, contingency tables, and the like.
One odd omission is R: the book covers procedures for SAS, SPSS, and Stata, but not R. The authors' website appears not to be updated since the 2nd edition, and also does not cover R. That is a puzzling lacuna given the growing popularity of R in general and especially in bioinformatics. However, it is not a crucial flaw, since LR in R is not difficult and there are many examples online.
In summary: if you're an applied researcher in medicine, public health, psychology, etc., and want to learn about LR, get it.