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...
| VerfasserInnen: | ; ; |
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| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
2020
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| In: |
Journal of quantitative criminology
Jahr: 2020, Band: 36, Heft: 2, Seiten: 371-394 |
| Online-Zugang: |
Volltext (Resolving-System) |
| Journals Online & Print: | Lade...
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| Verfügbarkeit prüfen: | HBZ Gateway |
| Schlagwörter: |
MARC
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| 520 | |a 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. | ||
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