The “Pliability” of Criminological Analyses: assessing Bias in Regression Estimates Using Monte Carlo Simulations

When biased coefficient and standard error estimates are published, they can result in inaccurate findings which might motivate ineffective—or harmful—policy choices and reduce the legitimacy of social scientific research. In this paper, we demonstrate how Monte Carlo simulations (MCS) can be used t...

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Detalles Bibliográficos
Autor principal: West, Matthew P. (Autor)
Otros Autores: Cohen, Mark A. ; Rorie, Melissa
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2020
En: Journal of quantitative criminology
Año: 2020, Volumen: 36, Número: 2, Páginas: 371-394
Acceso en línea: Volltext (Resolving-System)
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Palabras clave:
Estimation bias
Monte Carlo simulation
Regression
Replication
Descripción
Sumario:When biased coefficient and standard error estimates are published, they can result in inaccurate findings which might motivate ineffective—or harmful—policy choices and reduce the legitimacy of social scientific research. In this paper, we demonstrate how Monte Carlo simulations (MCS) can be used to evaluate potential bias in estimates.
ISSN:1573-7799
DOI:10.1007/s10940-018-9398-5