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Most social work researchers are familiar with linear regression techniques, which are fairly straightforward to conduct, interpret, and present. However, linear regression is not appropriate for discrete dependent variables, and social work research frequently employs these variables, focusing on outcomes such as placement in foster care or not; level of severity of elder abuse or depression symptoms; or number of reoffenses by juvenile delinquents in the year following adjudication.
This book presents detailed discussions of regression models that are appropriate for a variety of discrete dependent variables. The major challenges of such analyses lie in the non-linear relationships between independent and dependent variables, and particularly in interpreting and presenting findings. Clear language guides the reader briefly through each step of the analysis, using SPSS and result presentation to enhance understanding of the important link function. The book begins with a brief review of linear regression; next, the authors cover basic binary logistic regression, which provides a foundation for the other techniques. In particular, comprehension of the link function is vital in order to later interpret these methods' results. Though the book assumes a basic understanding of linear regression, reviews and definitions throughout provide useful reminders of important terms and their meaning, and throughout the book the authors provide detailed examples based on their own data, which readers may work through by accessing the data and output on companion website.
Social work and other social sciences faculty, students, and researchers who already have a basic understanding of linear regression but are not as familiar with the regression analysis of discrete dependent variables will find this straightforward pocket guide to be a terrific boon to their bookshelves.
For additional resources, visit http://www.oup.com/us/pocketguides.
- Sales Rank: #1961535 in Books
- Published on: 2009-03-25
- Original language: English
- Number of items: 1
- Dimensions: 5.50" h x .70" w x 8.20" l, .70 pounds
- Binding: Paperback
- 224 pages
About the Author
John G. Orme, Ph.D., and Terri Combs-Orme, Ph.D., are professors in the College of Social Work at the University of Tennessee.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Multiple regression with discrete dependent variable by Orme and Combs-Orme
By Dr. Gabriel Liberman
There are many books on regression analysis in the market, some also deal with discrete dependent variables as oppose to continuous, but this book seems to function as a hand-book or a manual which we all need whenever we run statistics of all kinds. In my work as a statistical consultant I face these needs all the time, but it is too difficult to open one of the heavy books on regression I have. Instead, I keep this one available and find out that it never disapponints me, always provides some answer. The authors go step by step into the statistics of discrete models, what they do in compare to standard linear regression models, how to make the right interpretation of the estimates, and how to use estimates for predicting probability. This is what I use when I want to explain results to scholars for whom I run statistics. I recommend the book for beginers as well as intermediates. Dr. Gabriel Liberman - Data-Graph Statistical Consulting at: [...] .
0 of 0 people found the following review helpful.
One Star
By MARCIA
Ordered the wrong book for research class, only offered forty five cent to return it.
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