Multiply robust matching estimators of average and quantile treatment effects.

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY Scandinavian Journal of Statistics Pub Date : 2023-03-01 Epub Date: 2022-03-13 DOI:10.1111/sjos.12585
Shu Yang, Yunshu Zhang
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引用次数: 0

Abstract

Propensity score matching has been a long-standing tradition for handling confounding in causal inference, however requiring stringent model assumptions. In this article, we propose novel double score matching (DSM) utilizing both the propensity score and prognostic score. To gain the protection of possible model misspecification, we posit multiple candidate models for each score. We show that the de-biasing DSM estimator achieves the multiple robustness property in that it is consistent if any one of the score models is correctly specified. We characterize the asymptotic distribution for the DSM estimator requiring only one correct model specification based on the martingale representations of the matching estimators and theory for local Normal experiments. We also provide a two-stage replication method for variance estimation and extend DSM for quantile estimation. Simulation demonstrates DSM outperforms single score matching and prevailing multiply robust weighting estimators in the presence of extreme propensity scores.

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平均治疗效果和量化治疗效果的乘法稳健匹配估计值。
倾向得分匹配一直是因果推断中处理混杂因素的传统方法,但需要严格的模型假设。在本文中,我们提出了利用倾向得分和预后得分进行双得分匹配(DSM)的新方法。为了防止可能出现的模型不规范,我们为每个评分提出了多个候选模型。我们的研究表明,去偏差 DSM 估计器具有多重鲁棒性特性,即如果任何一个评分模型被正确指定,它都是一致的。我们根据匹配估计器的马氏表示法和局部正态实验理论,描述了只需要一个正确模型说明的 DSM 估计器的渐近分布。我们还提供了一种用于方差估计的两阶段复制方法,并将 DSM 扩展用于量值估计。仿真结果表明,在存在极端倾向得分的情况下,DSM 优于单分匹配和流行的多重稳健加权估计器。
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来源期刊
Scandinavian Journal of Statistics
Scandinavian Journal of Statistics 数学-统计学与概率论
CiteScore
1.80
自引率
0.00%
发文量
61
审稿时长
6-12 weeks
期刊介绍: The Scandinavian Journal of Statistics is internationally recognised as one of the leading statistical journals in the world. It was founded in 1974 by four Scandinavian statistical societies. Today more than eighty per cent of the manuscripts are submitted from outside Scandinavia. It is an international journal devoted to reporting significant and innovative original contributions to statistical methodology, both theory and applications. The journal specializes in statistical modelling showing particular appreciation of the underlying substantive research problems. The emergence of specialized methods for analysing longitudinal and spatial data is just one example of an area of important methodological development in which the Scandinavian Journal of Statistics has a particular niche.
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