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

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)
    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.
    ISBN
    • 080394263X ((paperback))
    • 9780803942639 ((paperback))
    LCCN
    92042925
    OCLC
    27067328
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