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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Bibliographische Detailangaben
1. VerfasserIn: Thomas, Kyle J. (VerfasserIn)
Beteiligte: McGloin, Jean Marie ; Sullivan, Christopher J.
Medienart: Elektronisch Aufsatz
Sprache:Englisch
Veröffentlicht: 2019
In: Journal of quantitative criminology
Jahr: 2019, Band: 35, Heft: 4, Seiten: 631-662
Online-Zugang: Volltext (Resolving-System)
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Schlagwörter:
Theory testing
Unobserved bias
False positives
sensitivity analysis
Sensitivity analysis
Beschreibung
Zusammenfassung: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