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Matching on Generalized Propensity Scores with Continuous Exposures

连续暴露下基于广义倾向得分的匹配

In the context of a binary treatment, matching is a well-established approach in causal inference. However, in the context of a continuous treatment or exposure, matching is still underdeveloped. We propose an innovative matching approach to estimate an average causal exposure-response function under the setting of continuous exposures that relies on the generalized propensity score (GPS). Our approach maintains the following attractive features of matching: (a) clear…

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Evaluation of the health impacts of the 1990 Clean Air Act Amendments using causal inference and machine learning

利用因果推断与机器学习评估1990年《清洁空气法》修正案的健康影响

We develop a causal inference approach to estimate the number of adverse health events that were prevented due to changes in exposure to multiple pollutants attributable to a large-scale air quality intervention/regulation, with a focus on the 1990 Clean Air Act Amendments (CAAA). We introduce a causal estimand called the Total Events Avoided (TEA) by the regulation, defined as the difference in the number of health events expected under the no-regulation pollution exposures…

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Discovering Heterogeneous Exposure Effects Using Randomization Inference in Air Pollution Studies

利用随机化推断发现空气污染暴露效应的异质性

Several studies have provided strong evidence that long-term exposure to air pollution, even at low levels, increases risk of mortality. As regulatory actions are becoming prohibitively expensive, robust evidence to guide the development of targeted interventions to protect the most vulnerable is needed. In this article, we introduce a novel statistical method that (i) discovers subgroups whose effects substantially differ from the population mean, and (ii) uses…

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Estimating the Effects of Fine Particulate Matter on 432 Cardiovascular Diseases Using Multi-Outcome Regression With Tree-Structured Shrinkage

利用树状收缩多结局回归估计细颗粒物与432种心血管疾病的关系

The positive relationship between airborne fine particulate matter (PM2.5) and cardiovascular disease (CVD) is established. Little is known about effect size heterogeneity across distinct CVD outcomes. We conducted a multi-outcome case-crossover study of Medicare beneficiaries aged >65 years residing in the mainland USA from 2000 through 2012. The exposure was two-day average PM2.5 in each individual’s residential zipcode. The outcomes were hospitalization for 432 distinct…

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Hierarchical Models for Semicompeting Risks Data With Application to Quality of End-of-Life Care for Pancreatic Cancer

半竞争风险数据的层级模型:胰腺癌临终照护质量应用

Readmission following discharge from an initial hospitalization is a key marker of quality of healthcare in the United States. For the most part, readmission has been studied among patients with “acute” health conditions, such as pneumonia and heart failure, with analyses based on a logistic-Normal generalized linear mixed model. Naïve application of this model to the study of readmission among patients with “advanced” health conditions such as pancreatic cancer, however, is…

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Uncertainty in Propensity Score Estimation: Bayesian Methods for Variable Selection and Model-Averaged Causal Effects

倾向得分估计的不确定性:贝叶斯变量选择与模型平均因果效应

Causal inference with observational data frequently relies on the notion of the propensity score (PS) to adjust treatment comparisons for observed confounding factors. As decisions in the era of "big data" are increasingly reliant on large and complex collections of digital data, researchers are frequently confronted with decisions regarding which of a high-dimensional covariate set to include in the PS model in order to satisfy the assumptions necessary for estimating…

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An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio-Temporal Information

利用时空信息估计长期空气污染效应

There is substantial observational evidence that long-term exposure to particulate air pollution is associated with premature death in urban populations. Estimates of the magnitude of these effects derive largely from cross-sectional comparisons of adjusted mortality rates among cities with varying pollution levels. Such estimates are potentially confounded by other differences among the populations correlated with air pollution, for example, socioeconomic factors. An…

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Smooth quantile ratio estimation

平滑分位数比估计

We propose a novel approach to estimating the mean difference between two highly skewed distributions. The method, which we call smooth quantile ratio estimation, smooths, over percentiles, the ratio of the quantiles of the two distributions. The method defines a large class of estimators, including the sample mean difference, the maximum likelihood estimator under log-normal samples and the L-estimator. We derive asymptotic properties such as consistency and asymptotic…

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Improved Semiparametric Time Series Models of Air Pollution and Mortality

空气污染与死亡率的改进半参数时间序列模型

In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U. S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S–PLUS implementation of generalized additive…

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Meta-Analysis of Migraine Headache Treatments: Combining Information from Heterogeneous Designs

偏头痛治疗的元分析:整合异质研究设计的信息

Migraine headache is a common condition in the United States for which a wide range of drug and nondrug treatments are available. There is wide disagreement about which treatments are most effective; meta-analysis of existing clinical trials can help to bring existing evidence to bear on this question. Conducting a meta-analysis is a challenging statistical problem because of the absence of a uniform accepted definition of headache syndromes, the diversity of treatments, and…

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Meta-Analysis of Migraine Headache Treatments: Combining Information from Heterogeneous Designs

偏头痛治疗的元分析:融合异质研究设计的信息

Migraine headache is a common condition in the United States for which a wide range of drug and nondrug treatments are available. There is wide disagreement about which treatments are most effective; meta-analysis of existing clinical trials can help to bring existing evidence to bear on this question. Conducting a meta-analysis is a challenging statistical problem because of the absence of a uniform accepted definition of headache syndromes, the diversity of treatments, and…

AI 解读阅读原文 ↗BibTeX ↓