Quantifying the Likelihood of False Positives: Using Sensitivity Analysis to Bound Statistical Inference

Criminologists have long questioned how fragile our statistical inferences are to unobserved bias when testing criminological theories. This study demonstrates that sensitivity analyses offer a statistical approach to help assess such concerns with two empirical examples—delinquent peer influence an...

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Bibliographic Details
Authors: Thomas, Kyle J. (Author) ; McGloin, Jean Marie (Author) ; Sullivan, Christopher J. (Author)
Format: Electronic Article
Language:English
Published: 2019
In: Journal of quantitative criminology
Year: 2019, Volume: 35, Issue: 4, Pages: 631-662
Online Access: Volltext (Resolving-System)
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Summary:Criminologists have long questioned how fragile our statistical inferences are to unobserved bias when testing criminological theories. This study demonstrates that sensitivity analyses offer a statistical approach to help assess such concerns with two empirical examples—delinquent peer influence and school commitment.
ISSN:1573-7799
DOI:10.1007/s10940-018-9385-x