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Multilevel Analysis for Applied Research: It's Just Regression! (Methodology in the Social Sciences) ebook

by Robert Bickel


The regression approach is highly desirable as it builds on methods commonly taught in graduate programs in. .

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. For a one semester course in the social sciences, this book would make an excellent companion to more mathematically oriented texts. The American Statistician 2007-03-22).

Multi-level analyses based on data from 28,157 individuals in 27 countries support our theoretical reasoning

Multi-level analyses based on data from 28,157 individuals in 27 countries support our theoretical reasoning. The results of the regression analysis support the hypothesis that the observed decrease in airborne Ambrosia pollen may indeed be related to the presence of large numbers of O. communa in the Milan area, as the drastic decrease in airborne Ambrosia pollen in 2013 cannot be explained by meteorology alone.

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Methodology in the social sciences.

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. Methodology in the social sciences.

Methodology In The Social Sciences).

Guilford Publications.

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.
Naril
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.
SING
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.
Manesenci
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.
Anardred
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.
Iesha
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.
Multilevel Analysis for Applied Research: It's Just Regression! (Methodology in the Social Sciences) ebook
Author:
Robert Bickel
Category:
Medicine & Health Sciences
Subcat:
EPUB size:
1920 kb
FB2 size:
1312 kb
DJVU size:
1204 kb
Language:
Publisher:
The Guilford Press; 1 edition (March 20, 2007)
Pages:
355 pages
Rating:
4.9
Other formats:
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