Logistic Regression

Rating:
Summary: depends on what background you are coming from...
Review: I'm a physician learning about clinical research/biostatistics etc. I found that this book was extremely helpful in guiding me through basic rules, steps and theories on how to build a logistic regression model. The examples where straight forward, even for a person without a strong math background. However, I can also see that this would not be enough for a person set out to be a biostatistician, as this book would seem rather elementary. If you are a person with a so-so background in math and statistics, and are interested in learning to adequately perform statistical analyses with logistic regression, this is the book for you.

Rating:
Summary: Good for what it is
Review: This book has a specific goal. It's aim is to give a basic competence in the use of logistic regression, related techniques, and the software that deal with them. This, it does very well. By intent, it leaves many other needs unmet.

The format is 13 chapters, possibly representing the 13 or 14 weeks in a typical school term. Each chapter has a specific statement of teaching goals at the front, a summary outline of the course to date in the back, and a few pages of questions or exercises with answers. There appear to be sample data sets available, formatted for popular stats packages, but I did not figure out how they are made available. Within the main text of each chapter, every page reads like a blackboard lecture: equations on the left and narration on the right. The presentation uses a minimum of math, just a little algebra and exponentials in a few specific forms.

For the aspiring tool-user, this book may be worth a semester's tuition. I can fault it only for an annoying habit of writing out in words equations that appear on the same page ("e raised to the power of the sum of products ... ").

This book is NOT meant for people truly interested in the theory or practice of the exact computations. For example, its use of probability scarely mentions joint or conditional distributions. As a result, some of its formulas (e.g. p.48) come across as rote memorization, instead of natural expressions of the laws of probability. Lacking joint probability, the covariance matrix can not have meaning. It is just something produced, somehow, by an oracular computer program.

The repeated phrase, "according to statisticians ..." makes it very clear that statisticians are a breed distinct from intended audience. What they do is quite alien, but somehow, sometimes leaves the student with formulas to grind through.

Before you buy this book, be very clear about what you expect from it. Beginning students may get a lot from it. Readers already familiar with probability and some stats are likely to be disappointed.

Rating:
Summary: An excellent step-by-step text
Review: When Kleinbaum entitles his book "a self-learning text", this is TRUE ! I'm sure anyone can learn logistic regression with this book. It is cristal-clear, very progressive, with real-data examples... If the best teachers are those who make you feel you're intelligent, certainly the author must be a good teacher... because his book is ! I do recommend it warmly to anyone who has to teach (like me) or learn logistic regression.

Rating:
Summary: An excellent step-by-step text
Review: When Kleinbaum entitles his book "a self-learning text", this is TRUE ! I'm sure anyone can learn logistic regression with this book. It is cristal-clear, very progressive, with real-data examples... If the best teachers are those who make you feel you're intelligent, certainly the author must be a good teacher... because his book is ! I do recommend it warmly to anyone who has to teach (like me) or learn logistic regression.