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Multilevel Analysis for Applied Research: It's Just Regression! (Methodology in the Social Sciences) (Englisch) Taschenbuch – 26. April 2007


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Pressestimmen

"This book is one of the best statistical texts that I have ever read, and I would highly recommend using it for an advanced data analysis course. The examples and the step-by-step methods using SPSS are superb and statistically accurate. The author does a tremendous job of linking concepts to statistical procedures, as well as giving great examples! The listings for how to interpret the coefficients will really help graduate students make sense of their results." - Alison J. Bianchi, Department of Sociology, Kent State University "This would be a good reference for sticky issues, and I really like that this book addresses issues that researchers actually struggle with when they are working on a project, such as effective sample size and maximum likelihood. I also like the writing style - casual but authoritative." - Julia McQuillan, Bureau of Sociological Research and Department of Sociology, University of Nebraska-Lincoln "The writing style is excellent for students and for applied researchers who don't consider themselves experts in statistics. One of the particular strengths of the book is how the author writes about the interpretation of results that may lead to the respecification of models and their tests. The figures of the models tested, the to-do lists, and interpretation of the corresponding output allow readers to integrate cognitively the concepts and procedures pertaining to very difficult topics. It is clear that the author spent significant amounts of time considering how best to present this information. I would tell my colleagues who don't consider themselves experts in measurement and statistics to buy themselves a present - this book." - Jonna M. Kulikowich, Department of Educational and School Psychology and Special Education, Penn State "This is a lucid and well-written text that cuts directly to the important issues in multilevel modeling. The regression approach is highly desirable as it builds on methods commonly taught in graduate programs in the social sciences. The text is appropriate for graduate-level teaching and could easily be used as the primary text in a multilevel modeling seminar. In addition, applied researchers with a background in multiple regression will find this an excellent resource for modeling nested data in cross-sectional and longitudinal studies." - Jeffrey D. Long, Department of Educational Psychology, University of Minnesota "Unparalleled as an introduction to multilevel methods. For anyone who wants to learn or teach these methods using a text built on examples rather than equations, who prefers demonstrations over derivations, and who wants to begin analyzing data right away, this is the book to use." - Daniel Ozer, Department of Psychology, University of California, Riverside "With this rigorous and detailed book, Bickel provides an unparalleled introduction to multilevel methods. This is a practical text both for experienced researchers who need to catch up with these newer methods and for students who have completed a regression course and are ready for the next step. The approach taken is conceptual and data-analytic, with extended examples analyzed in detail. There is extensive use of tables and figures to display data and report the worked examples, and each chapter's brief discussion of additional resources and readings is very useful. All examples reference the SPSS software package, and specific instructions for using this software are included as boxed text that does not interrupt the flow of ideas but is easily found when needed. While the book is designed for the data analyst rather than the methodologist, technical issues are not ignored. For anyone who wants to learn or teach multilevel modeling using a text built on examples rather than equations, who prefers demonstrations over derivations, and who wants to begin analyzing data right away, this is the book to use." - Daniel Ozer, Department of Psychology, University of California, Riverside "This is a very accessible and terrifically useful book." - Lisa Feldman Barrett, PhD, Department of Psychology, Boston College "Great teachers are masters at taking inherently complicated topics and simplifying them into manageable ones that can be communicated with ease. In the case of [ital]Multilevel Analysis for Applied Research: It's Just Regression![/ital], great teaching comes in the form of a book...The author takes pride in presenting the topic in an understandable and straightforward manner that encourages the reader to keep reading...The author has done a nice job presenting complicated subject matter in a manner that promotes learning and, overall, the book was a great introduction to multilevel analysis." - Canadian Journal of Program Evaluation (Carl D. Westine, Vol. 25, No. 1, Spring 2010)

Synopsis

This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical techniques they already know, Robert Bickel emphasizes the parallels with more familiar regression models, shows how to do multilevel modeling using SPSS, and demonstrates how to interpret the results. He discusses the strengths and limitations of multilevel analysis and explains specific circumstances in which it offers (or does not offer) methodological advantages over more traditional techniques. Over 300 dataset examples from research on educational achievement, income attainment, voting behavior, and other timely issues are presented in numbered procedural steps.

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Amazon.com: 5 Rezensionen
3 von 3 Kunden fanden die folgende Rezension hilfreich
Helpful supplement 15. September 2012
Von LizzyBee - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
I bought this book because the MLM textbook for the course I was taking was too technical; I needed something with more concrete examples and clearer, less dense explanations. This fit the bill. I don't think this would work as your only resource, though - I used it to help clarify the concepts I had a limited grasp of after my professor's lectures.
8 von 11 Kunden fanden die folgende Rezension hilfreich
Teaching like 10. Juni 2007
Von Viviana Fernandez - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
A good book. Very good examples. I missed some reference to the mathematical derivations of the econometric techniques being used. Also, it would be nice that the data sets were available online.
9 von 14 Kunden fanden die folgende Rezension hilfreich
Mediocre 27. Juli 2008
Von Dennis Hanseman - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
There is a need for a text pitched at readers without strong statistical backgrounds. Unfortunately, this is not the one.

For some reason, the author feels defensive about multilevel methodology, and seems too spend much of the first several chapters apologizing for it. Beyond that, though, he jumps around too much -- for example, presenting results and promising to explain them later -- and fails to define key ideas (such as "nesting" and "contextual variables") Overall, it lacks focus.
5 von 9 Kunden fanden die folgende Rezension hilfreich
Might be good with appropriate data sets 21. Juni 2009
Von M. Matthews - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Before purchasing this book, I read previous reviews regarding the absence of data sets. Since publishing the book, the author has provided data sets on his website. Unfortunately, many of the data sets have similar names and cover similar material, and it is not always clear which data set the author is referring to within each section of the book. In addition, the variable names in the data sets do not match those in the book, and (often times) the variables in the book have been adjusted, such that they are slightly different from those provided in the online data sets.

All of this is important because the author spends A LOT of time explaining the data sets in his examples, and even provides step-by-step "guides" to running analyses that are based on his specific data sets. For me, it was annoying and distracting that I never knew if I was using the right data and variables. When purchasing it, I thought I could use this book to get the basic concepts of multilevel analysis down and that the use of the data sets was not needed, I was wrong. It is helpful to have a user-friendly guide when you are learning something new, and in the current state, this book is not user-friendly.

If the author would simply provide well named data sets that match those in the book (i.e., have the exact same variables and variable names), all of these problems could be fixed. However, it has been a while since the book was published, and he has not done this. I'd recommend finding another book if you want to really learn MLM.
4 von 11 Kunden fanden die folgende Rezension hilfreich
My Review 21. September 2007
Von Statz Dude - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
Oberall, this book is accessible to most graduate students of the social sciences. However, my only concern is where the heck can the reader get the same data sets as the procedures follow?! So, if you are buying this book for learning multilevel analysis, just realize that you do not have access to the data sets the author talks about.
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