NDLI: Analyzing Multiple-Item Measures of Crime and Deviance II: Tobit Regression Analysis of Transformed Scores

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Analyzing Multiple-Item Measures of Crime and Deviance II: Tobit Regression Analysis of Transformed Scores

Content Provider	Springer Nature Link
Author	Osgood, D. Wayne Finken, Laura L. McMorris, Barbara J.
Copyright Year	2002
Abstract	The purpose of this article is to inform criminological researchers about tobit regression, an alternative regression model that deserves more attention in this field. Tobit regression is intended for continuous data that are censored, or bounded at a limiting value. The tobit model may be a particularly good match to measures of self-reported offending, provided they have been transformed to reduce skewness. We present empirical analyses that evaluate the match of self-report measures to the assumptions of ordinary least square (OLS) and tobit regression models and that assess the consequences of any violations of assumptions. The analyses use a fourteen-item, self-report measure of delinquency from the Monitoring the Future study, a national survey of high school seniors. These analyses provide clear evidence that (1) transformations to reduce skewness improve the match of OLS to the data but still leave considerable discrepancies, and (2) the tobit model is well suited to the transformed measure. We conclude by assessing the purposes for which tobit offers greater and smaller advantages over OLS regression.
Starting Page	319
Ending Page	347
Page Count	29
File Format	PDF
ISSN	07484518
Journal	Journal of Quantitative Criminology
Volume Number	18
Issue Number	4
e-ISSN	15737799
Language	English
Publisher	Kluwer Academic Publishers-Plenum Publishers
Publisher Date	2002-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Statistics Criminology Methodology of the Social Sciences Sociology
Content Type	Text
Resource Type	Article
Subject	Law Pathology and Forensic Medicine

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