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Pocket Guide to Social Work Research Methods Ser.: Multiple Regression with Discrete Dependent Variables by John G. Orme and Terri Combs-Orme (2009, Trade Paperback)
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About this product
Product Identifiers
PublisherOxford University Press, Incorporated
ISBN-100195329457
ISBN-139780195329452
eBay Product ID (ePID)71143020
Product Key Features
Number of Pages256 Pages
LanguageEnglish
Publication NameMultiple Regression with Discrete Dependent Variables
Publication Year2009
SubjectSocial Work, Probability & Statistics / Regression Analysis, Statistics
TypeTextbook
AuthorJohn G. Orme, Terri Combs-Orme
Subject AreaMathematics, Social Science
SeriesPocket Guide to Social Work Research Methods Ser.
FormatTrade Paperback
Dimensions
Item Height0.6 in
Item Weight9.9 Oz
Item Length5.4 in
Item Width8.2 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2008-030809
Dewey Edition22
IllustratedYes
Dewey Decimal519.5/36
Table Of ContentPreface1. Introduction to Regression Modeling2. Regression with a Dichotomous Dependent Variable3. Regression with a Polytomous Dependent Variable4. Regression with an Ordinal Dependent Variable5. Regression with a Count Dependent VariableAppendix A: Description of Data SetsAppendix B: LogarithmsGlossary
SynopsisMost 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 yearfollowing adjudication. This book presents detailed discussions of regression models that are appropriate for a variety of discrete dependent variables. The major challenges of suchanalyses 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. Inparticular, 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 throughoutprovide 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 thisstraightforward pocket guide to be a terrific boon to their bookshelves. For additional resources, visit http://www.oup.com/us/pocketguides., Most social work researchers are familiar with linear regression, which is fairly straightforward to conduct, interpret, and present. However, linear regression is not appropriate for the discrete dependent variables frequently studied by the profession. This book presents methods for dichotomous, polytomous, ordinal, and count variables, with particular emphasis on interpreting and presenting results., 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., 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.
LC Classification NumberHV29.O76 2009
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