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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Bibliographic Details
Main Author: West, Matthew P. (Author)
Contributors: Cohen, Mark A. ; Rorie, Melissa
Format: Electronic Article
Language:English
Published: 2020
In: Journal of quantitative criminology
Year: 2020, Volume: 36, Issue: 2, Pages: 371-394
Online Access: Volltext (Resolving-System)
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Keywords:
Estimation bias
Monte Carlo simulation
Regression
Replication
Description
Summary: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