Skip to search
Skip to main content
Catalog
Help
Feedback
Your Account
Library Account
Bookmarks
(
0
)
Search History
Search in
Keyword
Title (keyword)
Author (keyword)
Subject (keyword)
Title starts with
Subject (browse)
Author (browse)
Author (sorted by title)
Call number (browse)
search for
Search
Advanced Search
Bookmarks
(
0
)
Princeton University Library Catalog
Start over
Cite
Send
to
SMS
Email
EndNote
RefWorks
RIS
Printer
Bookmark
Understanding regression assumptions / William D. Berry.
Author
Berry, William Dale
[Browse]
Format
Book
Language
English
Published/Created
Newbury Park : Sage Publications, ©1993.
Description
vii, 91 pages : illustrations ; 22 cm.
Availability
Available Online
SAGE Research Methods Core
Copies in the Library
Location
Call Number
Status
Location Service
Notes
Firestone Library - Stacks
HA31.3 .B47 1993
Browse related items
Request
Details
Subject(s)
Social sciences
—
Statistical methods
[Browse]
Regression analysis
[Browse]
Error analysis (Mathematics)
[Browse]
Series
Quantitative applications in the social sciences ; no. 07-092.
[More in this series]
Sage university papers series. Quantitative applications in the social sciences ; no. 07-092
Summary note
"Through the use of careful explanations and examples, Berry shows the reader how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project. Beginning with a brief review of the regression assumptions as they are typically presented in textbooks, Berry moves on to explore in detail the "substantive" meaning of each assumption (such as lack of measurement error, absence of specification error, linearity, homoscedasticity, and lack of autocorrelation). Aimed at improving social science applications of regression, this volume is a must for every student's and researcher's library."--Pub. desc.
Bibliographic references
Includes bibliographical references (p. 89-90).
Contents
1. Introduction
2. A formal presentation of the regression assumptions. The regression surface ; The role of the error term ; Other regression assumptions
3. A "weighty" illustration
4. The consequences of the regression assumptions being satisfied
5. The substantive meaning of regression assumptions. Drawing dynamic inferences from cross-sectional regressions ; The assumption of the absence of perfect multicollinearity ; The assumption that the error term is uncorrelated with each of the independent variables ; Specification error: using the wrong independent variables ; The assumption that the mean of the error term is zero ; Assumptions about level of measurement ; The assumption of measurement without error ; Random measurement error ; Nonrandom measurement error ; Proxy variables ; The assumptions of linearity and additivity ; The assumption of homoscedasticity and lack of autocorrelation ; The substantive meaning of autocorrelation ; The substantive meaning of homoscedasticity ; The consequences of heteroscedasticity and autocorrelation ; The assumption that the error term is normally distributed
6. Conclusion.
Show 3 more Contents items
ISBN
080394263X ((paperback))
9780803942639 ((paperback))
LCCN
92042925
OCLC
27067328
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Read more...
Other views
Staff view
Ask a Question
Suggest a Correction
Report Harmful Language
Supplementary Information
Other versions
Understanding regression assumptions [electronic resource] / William D. Berry.
id
99126771201706421
Understanding regression assumptions / William D. Berry.
id
SCSB-8856461