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添加75字节 、 2022年3月14日 (一) 11:39
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Unlike difference in differences approaches, this method can account for the effects of confounders changing over time, by weighting the control group to better match the treatment group before the intervention. Another advantage of the synthetic control method is that it allows researchers to systematically select comparison groups. It has been applied to the fields of political science, health policy, criminology, and economics.
 
Unlike difference in differences approaches, this method can account for the effects of confounders changing over time, by weighting the control group to better match the treatment group before the intervention. Another advantage of the synthetic control method is that it allows researchers to systematically select comparison groups. It has been applied to the fields of political science, health policy, criminology, and economics.
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综合控制方法是一种统计方法,用于评估比较案例研究中的干预措施的效果。它包括用作对照组的加权组合的构建,并与治疗组进行比较。这种比较被用来估计如果治疗组没有接受治疗会发生什么。与不同方法的差异不同,这种方法可以解释随时间变化的混杂因素的影响,通过加权对照组,以便在干预前更好地匹配治疗组。综合控制法的另一个优点是,它允许研究人员系统地选择对照组。它已应用于政治学、卫生政策、犯罪学和经济学等领域。
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'''合成对照'''方法是一种统计方法,用于评估比较案例研究中的干预措施的效果。它使用多组数据加权组合构建对照组,并与治疗组进行比较。这种比较被用来估计如果治疗组没有接受治疗会发生什么。与双重差分(Difference in difference)方法不同,这种方法可以纳入随时间变化的混杂因素的影响,通过调整对照组的加权系数,能更好地对干预前的治疗组数据进行匹配。合成对照的另一个优点是,它允许研究人员在多组候选数据中做系统性选择。它已应用于政治学、卫生政策、犯罪学和经济学等领域。
    
The synthetic control method combines elements from [[Matching (statistics)|matching]] and [[difference-in-differences]] techniques. Difference-in-differences methods are often-used policy evaluation tools that estimate the effect of an intervention at an aggregate level (e.g. state, country, age group etc.) by averaging over a set of unaffected units. Famous examples include studies of the employment effects of a raise in the [[Minimum wage in the United States|minimum wage]] in New Jersey fast food restaurants by comparing them to fast food restaurants just across the border in [[Philadelphia]] that were unaffected by a minimum wage raise,<ref name="CardKrueger">{{cite journal |last=Card |first=D. |authorlink=David Card |first2=A. |last2=Krueger |authorlink2=Alan Krueger |year=1994 |title=Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania |journal=[[American Economic Review]] |volume=84 |issue=4 |pages=772–793 |jstor=2118030 }}</ref> and studies that look at [[crime rates]] in southern cities to evaluate the impact of the [[Mariel boat lift]] on crime.<ref>{{cite journal |last=Card |first=D. |year=1990 |title=The Impact of the Mariel Boatlift on the Miami Labor Market |journal=[[Industrial and Labor Relations Review]] |volume=43 |issue=2 |pages=245–257 |doi=10.1177/001979399004300205 |url=http://arks.princeton.edu/ark:/88435/dsp016h440s46f }}</ref>  The control group in this specific scenario can be interpreted as a [[Weighted arithmetic mean|weighted average]], where some units effectively receive zero weight while others get an equal, non-zero weight.
 
The synthetic control method combines elements from [[Matching (statistics)|matching]] and [[difference-in-differences]] techniques. Difference-in-differences methods are often-used policy evaluation tools that estimate the effect of an intervention at an aggregate level (e.g. state, country, age group etc.) by averaging over a set of unaffected units. Famous examples include studies of the employment effects of a raise in the [[Minimum wage in the United States|minimum wage]] in New Jersey fast food restaurants by comparing them to fast food restaurants just across the border in [[Philadelphia]] that were unaffected by a minimum wage raise,<ref name="CardKrueger">{{cite journal |last=Card |first=D. |authorlink=David Card |first2=A. |last2=Krueger |authorlink2=Alan Krueger |year=1994 |title=Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania |journal=[[American Economic Review]] |volume=84 |issue=4 |pages=772–793 |jstor=2118030 }}</ref> and studies that look at [[crime rates]] in southern cities to evaluate the impact of the [[Mariel boat lift]] on crime.<ref>{{cite journal |last=Card |first=D. |year=1990 |title=The Impact of the Mariel Boatlift on the Miami Labor Market |journal=[[Industrial and Labor Relations Review]] |volume=43 |issue=2 |pages=245–257 |doi=10.1177/001979399004300205 |url=http://arks.princeton.edu/ark:/88435/dsp016h440s46f }}</ref>  The control group in this specific scenario can be interpreted as a [[Weighted arithmetic mean|weighted average]], where some units effectively receive zero weight while others get an equal, non-zero weight.
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