Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) (Paperback)

by Jos W. R. Twisk (Author) "The popularity of applying multilevel analysis has increased rapidly over the past 10 years..." (more)
Key Phrases: covariance between the random intercept, multivariate multilevel analysis, different medical doctors, Refresh Categories, Help Name, Parameter Estimates (more...)

Editorial Reviews

Review
'... a concise practical guide for non-mathematical researchers beginning to use this technique in their work.' Pradeep Malakar, Institute Food Research

Product Description
This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians; those books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the practical application of multilevel analysis in research. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyze the data. This approach will help bridge the conceptual and communication gap that exists between researchers and statisticians.

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Product Details

• Paperback: 196 pages
• Publisher: Cambridge University Press; 1 edition (May 15, 2006)
• Language: English
• ISBN-10: 0521614988
• ISBN-13: 978-0521614986
• Product Dimensions: 9.6 x 6.8 x 0.5 inches
• Shipping Weight: 15.5 ounces (View shipping rates and policies)
• Average Customer Review: 4.5 out of 5 stars See all reviews (4 customer reviews)
• Amazon.com Sales Rank: #327,001 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

1 of 1 people found the following review helpful:

3.0 out of 5 stars Enough for you to get acquainted with these models, January 10, 2007

By	VSOP (Pelotas, Brazil) - See all my reviews

This review is from: Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) (Hardcover)

The book is easy to understand and presents a series of situations where multilevel models are applied, in the context of epidemiological analysis. The examples are mostly very simple, and I don't think the book will help if you want to fit models. If you want to understand them better, then it may be of use. I have some other restrictions as well - some concepts presented in chapter 2 (section 2.8.1) are in direct contradiction with MLwiN user's guide (version 2, 2005, section 7.5, p.86). My understanding is that the latter is correct. Also, a model fitted in chapter 3 with a dichotomous variable random at level 2 includes the covariance parameter, what looks wrong to me. All in all, I think there are better options for an introductory text, e. g. Snijders & Bosker (1999).

1 of 1 people found the following review helpful:

5.0 out of 5 stars A friendly guilde to multilevel analysis, November 5, 2006

By	Adolf "Liao" (Taiwan) - See all my reviews

Twisk's work is very good for those who are not experts in mathematics and would like to apply this statistic method for investigating cluster effect. Through the tutorial journey mainly illustrated by MLwiN, readers can easily catch the general picture of multilevel analysis and make sense of interpretation and application. The comparison of different statistic software used in multilevel analysis and the concise text for power analysis were another two precious gifts the author gave us.

5.0 out of 5 stars great in describing the motivation of multilevel analysis, March 22, 2009

By	Sunny (Raleigh, NC) - See all my reviews

This book accomplishes its goal. It does not seek to describe the statistical details of multilevel analysis (hierarchical models/mixed models). It clearly motivates when these analyses should be used. The author cites several other texts that go over details, but believes that the literature lacks a descriptive overview of these methods. The book served this purpose for me.