Robust post-matching inference

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August undefined, 2024

WebRobust Post-Matching Inference Author: Alberto Abadie, Jann Spiess Source: Journal of the American Statistical Association 2024 v.117 no.538 pp. 983-995 ISSN: 1537-274X Subject: Americans, confidence interval, empirical research, journals, models, observational studies, regression analysis Abstract: WebMar 21, 2024 · Although there has been some debate about their utility (King and Roberts 2015), robust SEs rarely degrade inferences and often improve them. Generally, robust SEs must be used when any non-uniform weights are included in the estimation (e.g., with matching with replacement or inverse probability weighting). Cluster-robust standard errors.

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Web" Robust Post-Matching Inference ," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117 (538), pages 983-995, April. Alberto Abadie & Matias D. Cattaneo, 2024. WebWe show that two easily implementable alternatives produce approximations to the distribution of the post-matching estimator that are robust to misspecification. A … erik the red accomplishments

drtmle: Doubly-Robust Inference in R

WebOct 23, 2024 · Robust Post-Matching Inference Nearest-neighbor matching is a popular nonparametric tool to create balance between treatment and control groups in … Webbased abductive approaches to inference (Moldovan et al., 2003; Raina et al., 2005b), we adopt a graph-based representation of sentences, and use graph matching approach to … WebJan 14, 2024 · Robust Post-Matching Inference Journal of the American Statistical Association ( IF 4.369 ) Pub Date: 2024-01-14 , DOI: 10.1080/01621459.2024.1840383 … erik theory

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Using Propensity Scores for Causal Inference: Pitfalls and Tips

WebMar 31, 2015 · Instead, if the number of clusters is large, statistical inference after OLS should be based on cluster-robust standard errors. We outline the basic method as well as many complications that can arise in practice. These include cluster-specific fixed effects, few clusters, multiway clustering, and estimators other than OLS. WebJul 27, 2024 · This paper proves that local projection inference robustly handles two issues that commonly arise in applications: highly persistent data and the estimation of impulse … erik theory of developmentWebJan 2, 2024 · The proposed robust inference for federated meta-learning (RIFL) methodology is broadly applicable and illustrated with three inference problems: aggregation of parametric models, high-dimensional prediction models, and inference for average treatment effects. erik the red boat

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Robust post-matching inference

An Ultimate Guide to Matching and Propensity Score Matching

WebApr 12, 2024 · Towards Robust Tampered Text Detection in Document Image: New dataset and New Solution ... Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation ... CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning WebRobust Post-Matching Inference. Nearest-neighbor matching is a popular nonparametric tool to create balance between treatment and control groups in observational studies. …

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WebSep 17, 2024 · The advantage matching has over regression, and the reason why I think it is so valuable and why I devoted my graduate training to understanding and improving … WebOct 1, 2024 · And it is more robust than that of Zhang and Zhang (2014). Note that all methods cannot identify the correct model in the model selection step when the signals are weak, but post-selection methods are still able to carry out valid statistical inference.

WebOct 20, 2024 · There are (at least) three sources of uncertainty when performing a propensity score matching analysis: 1) the estimation of the PS, 2) the matching, and 3) … WebImplementation of doubly-robust inference The main function of the package is the eponymous drtmle function. This function estimates the treatment-specific marginal mean for user-specified levels of a discrete-valued treatment and computes a doubly-robust covariance matrix for these estimates.

WebRobust Post-Matching Inference Alberto Abadie Jann Spiess MIT Stanford University October 2024 Abstract Nearest-neighbor matching is a popular nonparametric tool to … WebDec 13, 2024 · This dissertation is comprised of three essays that apply machine learning and high-dimensional statistics to causal inference. The first essay proposes a parametric alternative to the synthetic...

WebJan 20, 2024 · We will develop a new, robust marginal structural quantile model to draw simultaneous causal inference about longitudinal treatments across the entire distribution of outcomes and further improve the flexibility of …

WebRobust Post-Matching Inference Journal of the American Statistical Association, 117 (538), 983-995. Alberto Abadie with J. Spiess January 2024 Econometrics A Penalized Synthetic … erik the red biography \u0026 facts britannicaWebAll types of matching are special cases with discrete weights What matching and weighting methods can do: ﬂexible and robust causal modeling underselection on observables What they cannot do: eliminate bias due tounobserved confounding Kosuke Imai (Princeton) Matching and Weighting Methods Duke (January 18 – 19, 2013) 4 / 57 find the zeroes of the cubic polynomialWebJan 25, 2024 · Matching The goal of matching is to reduce the bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one (or more) non-treated unit (s) with similar observable characteristics against which the covariates are balanced out. erik the red backgroundWebApr 12, 2024 · Towards Robust Tampered Text Detection in Document Image: New dataset and New Solution ... Self-Correctable and Adaptable Inference for Generalizable Human … erik the red britannicaWebJan 11, 2024 · Robust inference with knockoffs. We consider the variable selection problem, which seeks to identify important variables influencing a response out of many candidate … erik the red birth and deathWebRobust Post-Matching Inference Journal of the American Statistical Association Volume 117, 2024 - Issue 538 3,136 Views 24 CrossRef citations to date 0 Altmetric Theory and Methods Robust Post-Matching Inference Alberto Abadie & Jann Spiess erik the red bornWebprocedure. A double-robust estimator gives the analyst two opportunities for ob-taining unbiased inference when adjusting for selection eﬀects such as confounding by allowing for diﬀerent forms of model misspeciﬁcation; a double-robust estima-tor also can oﬀer increased eﬃciency when all the models are correctly speciﬁed. erik the good