This paper provides a selective review of the recent developments on econometric/statistical modeling in quantile treatment effects under both selection on observables and on unobservables.First,we discuss identificat...This paper provides a selective review of the recent developments on econometric/statistical modeling in quantile treatment effects under both selection on observables and on unobservables.First,we discuss identification,estimation and inference of quantile treatment effects under the framework of selection on observables.Then,we consider the case where the treatment variable is endogenous or self-selected,for which an instrumental variable method provides a powerful tool to tackle this problem.Finally,some extensions are discussed to the data-rich environments,to the regression discontinuity design,and some other approaches to identify quantile treatment effects are also discussed.In particular,some future research works in this area are addressed.展开更多
目的利用SAS开发的CAUSALTRT过程,实现三类估计方法的因果效应估计。方法采用SmokingWeight数据集,以戒烟为处理变量,体重变化为结局变量,其他因素为混杂变量,通过增强逆概率加权法(augmented inverse probability weighting,AIPW)对平...目的利用SAS开发的CAUSALTRT过程,实现三类估计方法的因果效应估计。方法采用SmokingWeight数据集,以戒烟为处理变量,体重变化为结局变量,其他因素为混杂变量,通过增强逆概率加权法(augmented inverse probability weighting,AIPW)对平均处理效应(the average treatment effect,ATE)进行估计,通过回归调整法(regression adjustment,REGADJ)对处理组平均处理效应(the average treatment effect for the treated,ATT)进行估计。结果戒烟对体重变化的ATE和ATT分别为3.209(95%CI:2.232~4.187)和3.276(95%CI:2.332~4.219)。结论CAUSALTRT可以实现不同的因果效应估计,但应用时需要考虑其是否满足前提假设以及注意事项。展开更多
BACKGROUND Right-sided ligamentum teres(RSLT)is often associated with portal venous anomalies(PVA)and is regarded as a concerning feature for hepatobiliary intervention.Most studies consider RSLT to be one of the caus...BACKGROUND Right-sided ligamentum teres(RSLT)is often associated with portal venous anomalies(PVA)and is regarded as a concerning feature for hepatobiliary intervention.Most studies consider RSLT to be one of the causes of left-sided gallbladder(LGB),leading to the hypothesis that LGB must always be present with RSLT.However,some cases have shown that right-sided gallbladder(RGB)can also be present in livers with RSLT.AIM To highlight the rare variation that RSLT may not come with LGB and to determine whether ligamentum teres(LT)or gallbladder location is reliable to predict PVA.METHODS This study retrospectively assessed 8552 contrast-enhanced abdominal computed tomography examinations from 2018 to 2021[4483 men,4069 women;mean age,59.5±16.2(SD)years].We defined the surrogate outcome as major PVAs.The cases were divided into 4 subgroups according to gallbladder and LT locations.On one hand,we analyzed PVA prevalence by LT locations using gallbladder location as a controlled variable(n=36).On the other hand,we controlled LT location and computed PVA prevalence by gallbladder locations(n=34).Finally,we investigated LT location as an independent factor of PVA by using propensity score matching(PSM)and inverse probability of treatment weighting(IPTW).RESULTS We found 9 cases of RSLT present with RGB.Among the LGB cases,RSLT is associated with significantly higher PVA prevalence than typical LT[80.0%vs 18.2%,P=0.001;OR=18,95%confidence interval(CI):2.92-110.96].When RSLT is present,we found no statistically significant difference in PVA prevalence for RGB and LGB cases(88.9%vs 80.0%,P>0.99).Both PSM and IPTW yielded balanced cohorts in demographics and gallbladder locations.The RSLT group had a significantly higher PVA prevalence after adjusted by PSM(77.3%vs 4.5%,P<0.001;OR=16.27,95%CI:2.25-117.53)and IPTW(82.5%vs 4.7%,P<0.001).CONCLUSION RSLT doesn't consistently coexist with LGB.RSLT can predict PVA independently while the gallbladder location does not serve as a sufficient predictor.展开更多
In this paper, the estimation of average treatment effects is considered when we have the model information of the conditional mean and conditional variance for the responses given the covariates. The quasi-likelihood...In this paper, the estimation of average treatment effects is considered when we have the model information of the conditional mean and conditional variance for the responses given the covariates. The quasi-likelihood method adapted to treatment effects data is developed to estimate the parameters in the conditional mean and conditional variance models. Based on the model information, we define three estimators by imputation, regression and inverse probability weighted methods. All the estimators are shown asymptotically normal. Our simulation results show that by using the model information, the substantial efficiency gains are obtained which are comparable with the existing estimators.展开更多
Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score...Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score method by Imai and Ratkovic(2014),the stable balance weighting procedure by Zubizarreta(2015),the calibration balance weighting approach by Chan,et al.(2016),and the integrated propensity score technique by Sant’Anna,et al.(2020).Simulations are conducted to illustrate the finite sample performance of both the average treatment effect and quantile treatment effect estimators based on different weighting methods.Simulation results show that in general,the covariate balance weighting methods can outperform the conventional maximum likelihood estimation method while the performance of the four covariate balance weighting methods varies with the data generating processes.Finally,the four covariate balance weighting methods are applied to estimate the treatment effects of the college graduate on personal annual income.展开更多
基金Supported by the National Natural Science Foundation of China#71631004(Key Project)the National Science Fund for Distinguished Young Scholars#71625001the scholarship from China Scholarship Council(CSC)under the Grant CSC N201806310088.
文摘This paper provides a selective review of the recent developments on econometric/statistical modeling in quantile treatment effects under both selection on observables and on unobservables.First,we discuss identification,estimation and inference of quantile treatment effects under the framework of selection on observables.Then,we consider the case where the treatment variable is endogenous or self-selected,for which an instrumental variable method provides a powerful tool to tackle this problem.Finally,some extensions are discussed to the data-rich environments,to the regression discontinuity design,and some other approaches to identify quantile treatment effects are also discussed.In particular,some future research works in this area are addressed.
文摘目的利用SAS开发的CAUSALTRT过程,实现三类估计方法的因果效应估计。方法采用SmokingWeight数据集,以戒烟为处理变量,体重变化为结局变量,其他因素为混杂变量,通过增强逆概率加权法(augmented inverse probability weighting,AIPW)对平均处理效应(the average treatment effect,ATE)进行估计,通过回归调整法(regression adjustment,REGADJ)对处理组平均处理效应(the average treatment effect for the treated,ATT)进行估计。结果戒烟对体重变化的ATE和ATT分别为3.209(95%CI:2.232~4.187)和3.276(95%CI:2.332~4.219)。结论CAUSALTRT可以实现不同的因果效应估计,但应用时需要考虑其是否满足前提假设以及注意事项。
基金reviewed and approved by the Institutional Review Board I&II of Taichung Veterans General Hospital(Approval No.TCVGH-IRB No.CE22408B).
文摘BACKGROUND Right-sided ligamentum teres(RSLT)is often associated with portal venous anomalies(PVA)and is regarded as a concerning feature for hepatobiliary intervention.Most studies consider RSLT to be one of the causes of left-sided gallbladder(LGB),leading to the hypothesis that LGB must always be present with RSLT.However,some cases have shown that right-sided gallbladder(RGB)can also be present in livers with RSLT.AIM To highlight the rare variation that RSLT may not come with LGB and to determine whether ligamentum teres(LT)or gallbladder location is reliable to predict PVA.METHODS This study retrospectively assessed 8552 contrast-enhanced abdominal computed tomography examinations from 2018 to 2021[4483 men,4069 women;mean age,59.5±16.2(SD)years].We defined the surrogate outcome as major PVAs.The cases were divided into 4 subgroups according to gallbladder and LT locations.On one hand,we analyzed PVA prevalence by LT locations using gallbladder location as a controlled variable(n=36).On the other hand,we controlled LT location and computed PVA prevalence by gallbladder locations(n=34).Finally,we investigated LT location as an independent factor of PVA by using propensity score matching(PSM)and inverse probability of treatment weighting(IPTW).RESULTS We found 9 cases of RSLT present with RGB.Among the LGB cases,RSLT is associated with significantly higher PVA prevalence than typical LT[80.0%vs 18.2%,P=0.001;OR=18,95%confidence interval(CI):2.92-110.96].When RSLT is present,we found no statistically significant difference in PVA prevalence for RGB and LGB cases(88.9%vs 80.0%,P>0.99).Both PSM and IPTW yielded balanced cohorts in demographics and gallbladder locations.The RSLT group had a significantly higher PVA prevalence after adjusted by PSM(77.3%vs 4.5%,P<0.001;OR=16.27,95%CI:2.25-117.53)and IPTW(82.5%vs 4.7%,P<0.001).CONCLUSION RSLT doesn't consistently coexist with LGB.RSLT can predict PVA independently while the gallbladder location does not serve as a sufficient predictor.
文摘In this paper, the estimation of average treatment effects is considered when we have the model information of the conditional mean and conditional variance for the responses given the covariates. The quasi-likelihood method adapted to treatment effects data is developed to estimate the parameters in the conditional mean and conditional variance models. Based on the model information, we define three estimators by imputation, regression and inverse probability weighted methods. All the estimators are shown asymptotically normal. Our simulation results show that by using the model information, the substantial efficiency gains are obtained which are comparable with the existing estimators.
基金the National Natural Science Foundation of China under Grant Nos.71631004 and 72033008the National Science Foundation for Distinguished Young Scholars under Grant No.71625001the Science Foundation of Ministry of Education of China under Grant No.19YJA910003。
文摘Different covariate balance weighting methods have been proposed by researchers from different perspectives to estimate the treatment effects.This paper gives a brief review of the covariate balancing propensity score method by Imai and Ratkovic(2014),the stable balance weighting procedure by Zubizarreta(2015),the calibration balance weighting approach by Chan,et al.(2016),and the integrated propensity score technique by Sant’Anna,et al.(2020).Simulations are conducted to illustrate the finite sample performance of both the average treatment effect and quantile treatment effect estimators based on different weighting methods.Simulation results show that in general,the covariate balance weighting methods can outperform the conventional maximum likelihood estimation method while the performance of the four covariate balance weighting methods varies with the data generating processes.Finally,the four covariate balance weighting methods are applied to estimate the treatment effects of the college graduate on personal annual income.
