Some recent developments in modeling quantile treatment effects

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.

Predicting portal venous anomalies by left-sided gallbladder or rightsided ligamentum teres hepatis: A large scale, propensity scorematched study

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.

Comparison of Covariate Balance Weighting Methods in Estimating Treatment Effects

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.