全球智库信息集成服务系统(G2TT): Evaluating Methods to Estimate the Effect of State Laws on Firearm Deaths: A Simulation Study

G2TT

来源类型	Research Reports
规范类型	报告
DOI	https://doi.org/10.7249/RR2685
ISBN	9781977401557
来源ID	RR-2685-RC
	Evaluating Methods to Estimate the Effect of State Laws on Firearm Deaths: A Simulation Study
	Terry L. Schell; Beth Ann Griffin; Andrew R. Morral
发表日期	2018
出版年	2018
页码	112
语种	英语
结论	Simulation results reveal that many commonly used modeling approaches in gun policy research have quite poor type 1 error rates. Several models have type 1 error rates ten times greater than the nominal α = 0.05 that was intended. Huber and cluster adjustments often do not fix these problems, and Huber adjustments can sometimes make them worse. The models also had surprisingly low statistical power to detect an effect-sized equivalent to a change of 1,000 deaths per year if a law were implemented nationally. Most models could correctly reject the null hypothesis only about 10 percent of the time with this true effect. With power this low, a large fraction of effects that are statistically significant will be found to be in the opposite direction as the true effect, and all significant effects will greatly exaggerate the magnitude of the true effect. One model was identified as having the best performance across all assessed criteria. This model is a negative binomial model of firearm deaths that includes time-fixed effects, an autoregressive effect, and change coding for the law effect. The preferred specification includes no state-fixed effects or standard error adjustment.
摘要	Researchers should consider using Bayesian statistical methods when estimating the effect of state laws on firearm death rates. Given the lack of power to conduct traditional significant testing, policymakers will be well served to understand the range of possible effects associated with a given policy and where the weight of current evidence lies. To correctly estimate the uncertainty in the model estimates, the models may need to include an autoregressive term. However, this requires careful consideration of how effects are coded to avoid dramatically biased effect estimates.
主题	Crime and Violence Prevention ; Firearms ; Gun Violence ; Public Safety Legislation ; Statistical Analysis Methodology
URL	https://www.rand.org/pubs/research_reports/RR2685.html
来源智库	RAND Corporation (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/108926
推荐引用方式 GB/T 7714	Terry L. Schell,Beth Ann Griffin,Andrew R. Morral. Evaluating Methods to Estimate the Effect of State Laws on Firearm Deaths: A Simulation Study. 2018.

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