Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) [Paperback] Author: Jos W. R. Twisk | Language: English | ISBN:
0521614988 | Format: PDF, EPUB
Applied Multilevel Analysis: A Practical Guide for Medical Researchers Download for free books Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) [Paperback] for everyone book mediafire, rapishare, and mirror link
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.
Download latest books on mediafire and other links compilation Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) [Paperback]
- Series: Practical Guides to Biostatistics and Epidemiology
- Paperback: 196 pages
- Publisher: Cambridge University Press; 1 edition (May 15, 2006)
- Language: English
- ISBN-10: 0521614988
- ISBN-13: 978-0521614986
- Product Dimensions: 9.8 x 6.7 x 0.4 inches
- Shipping Weight: 15.5 ounces (View shipping rates and policies)
- Amazon Best Sellers Rank: #921,967 in Books (See Top 100 in Books)
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).
By VSOP
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.
By Sunny
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