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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Detalles Bibliográficos
Autor principal: Thomas, Kyle J. (Autor)
Otros Autores: McGloin, Jean Marie ; Sullivan, Christopher J.
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2019
En: Journal of quantitative criminology
Año: 2019, Volumen: 35, Número: 4, Páginas: 631-662
Acceso en línea: Volltext (Resolving-System)
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Palabras clave:
False positives
Sensitivity analysis
Theory testing
Unobserved bias
sensitivity analysis
Descripción
Sumario: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