Recent advances in statistical methodologies in evaluating program for high-dimensional data

The era of big data brings opportunities and challenges to developing new statistical methods and models to evaluate social programs or economic policies or interventions. This paper provides a comprehensive review on some recent advances in statistical methodologies and models to evaluate programs with high-dimensional data. In particular, four kinds of methods for making valid statistical inferences for treatment effects in high dimensions are addressed. The first one is the so-called doubly robust type estimation, which models the outcome regression and propensity score functions simultaneously. The second one is the covariate balance method to construct the treatment effect estimators. The third one is the sufficient dimension reduction approach for causal inferences. The last one is the machine learning procedure directly or indirectly to make statistical inferences to treatment effect. In such a way, some of these methods and models are closely related to the de-biased Lasso type methods for the regression model with high dimensions in the statistical literature. Finally, some future research topics are also discussed.

光子嫩肤联合超脉冲CO2点阵激光治疗光老化皮肤的临床疗效

目的探讨光子嫩肤联合超脉冲CO2点阵激光治疗光老化皮肤的临床疗效。方法2017年10月至2018年4月,面部皮肤光老化患者118例,按治疗方法不同分为两组,对照组患者48例,采用光子嫩肤治疗,Ⅱ、Ⅲ型、Ⅳ型光老化皮肤分别选择波长580980 nm、7001200 nm的手具,和适当的能量密度、脉宽;联合组患者70例,在光子嫩肤基础上给予超脉冲CO2点阵激光治疗,选用Deep FX、Active FX手具。连续治疗5个疗程后观察两组患者肤质松弛程度、毛细血管扩张程度、毛孔粗大程度、色素沉着程度的情况,以及治疗后6个月治疗效果维持的满意度。结果治疗后联合组肤质松弛、毛细血管扩张、毛孔粗大、色素沉着评分分别为(2.47±0.5)分、(1.79±0.4)分、(2.00±0.6)分、(1.63±0.4)分,明显低于对照组的(3.30±0.6)分、(2.23±0.6)分、(3.04±0.7)分、(2.08±0.6)分(P<0.05)。联合组肤质松弛、毛细血管扩张、毛孔粗大、色素沉着治疗有效率分别为88.6%、91.4%、87.1%、90.0%,明显高于对照组的72.9%、75.0%、70.8%、75.0%(P<0.05)。联合组半年后满意度为82.9%,明显高于对照组的64.6%相比明显高(P<0.05)。结论光子嫩肤联合超脉冲CO2点阵激光应用,有助于改善光老化皮肤症状,提高临床治疗疗效及患者满意度。