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作者：Zhang, Jeffrey; Lee, Junu
作者单位：University of Pennsylvania
摘要：In real-world studies, the collected confounders may suffer from measurement error. Although mismeasurement of confounders is typically unintentional (originating from sources such as human oversight or imprecise machinery), deliberate mismeasurement also occurs and is becoming increasingly more common. For example, in the 2020 U.S. census, noise was added to measurements to assuage privacy concerns. Sensitive variables such as income or age are often partially censored and are only known up t...
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作者：Blackwell, M.; Pashley, N. E.
作者单位：Harvard University; Rutgers University System; Rutgers University New Brunswick
摘要：Factorial experiments are ubiquitous in the social and biomedical sciences, but when units fail to comply with each assigned factor, identification and estimation of the average treatment effects become impossible without strong assumptions. Leveraging an instrumental variables approach, previous studies have shown how to define and estimate the causal effect of treatment uptake among respondents who comply with treatment. A major caveat is that these results rely on strong assumptions on the ...
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作者：Bolin, David; Saduakhas, Damilya; Simas, Alexandre B.
作者单位：King Abdullah University of Science & Technology; King Abdullah University of Science & Technology
摘要：The modelling of spatial point processes has advanced considerably, yet extending these models to non-Euclidean domains, such as road networks, remains a challenging problem. We propose a novel framework for log-Gaussian Cox processes on general compact metric graphs by leveraging Gaussian Whittle-Mat & eacute;rn fields, which are solutions to fractional-order stochastic differential equations on metric graphs. To achieve computationally efficient likelihood-based inference, we introduce a num...
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作者：Dharamshi, A.; Neufeld, A.; Gao, L. L.; Witten, D.; Bien, J.
作者单位：University of Washington; University of Washington Seattle; Williams College; University of British Columbia; University of Washington; University of Washington Seattle; University of Southern California
摘要：Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In the special case of an $ n\times p $ random matrix with independent and identically distributed $ N_{p}(\mu,\Sigma) $ rows, Dharamshi et al. (2026)provided a comprehensive analysis of the settings in which thinning is or is not possible: briefly, if $ \Sigma $ is unknown then one can thin provided that $ n \gt 1 $. How...
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作者：Chopin, Nicolas; Crucinio, Francesca R.; Singh, Sumeetpal S.
作者单位：Institut Polytechnique de Paris; ENSAE Paris; University of Turin; University of Wollongong
摘要：Given a smooth function $ f $, we develop a general approach to turn Monte Carlo samples with expectation $ m $ into an unbiased estimate of $ f(m) $. Specifically, we develop estimators that are based on randomly truncating the Taylor series expansion of $ f $ and estimating the coefficients of the truncated series. We derive their properties and propose a strategy to set their tuning parameters (which depend on $ m $) automatically, with a view to making the whole approach simple to use. We ...
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作者：Schkoda, D.; Drton, M.
作者单位：Technical University of Munich
摘要：The field of causal discovery develops model selection methods to infer cause-effect relations among a set of random variables. For this purpose, different modelling assumptions have been proposed to render cause-effect relations identifiable. One prominent assumption is that the joint distribution of the observed variables follows a linear non-Gaussian structural equation model. In this paper, we develop novel goodness-of-fit tests that assess the validity of this assumption in the basic sett...
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作者：Du, Jin-Hong; Roeder, Kathryn; Wasserman, Larry
作者单位：University of Hong Kong; University of Hong Kong; Carnegie Mellon University
摘要：Data integration methods aim to extract low-dimensional embeddings from high-dimensional outcomes to remove unwanted variation, such as batch effects and unmeasured covariates, across heterogeneous datasets. However, multiple hypothesis testing after integration can be biased due to data-dependent processes. We introduce a robust post-integrated inference method that accounts for latent heterogeneity by leveraging control outcomes. Using causal interpretations, we derive nonparametric identifi...
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作者：Hines, Oliver J.; Diaz-Ordaz, Karla; Vansteelandt, Stijn
作者单位：Columbia University; University of London; University College London; Ghent University
摘要：The average treatment effect is commonly used to quantify the main effect of a binary treatment on an outcome. Extensions to continuous treatments are usually based on the dose-response curve or shift interventions, but both require strong overlap conditions, and the resulting curves may be difficult to summarize. This article focuses instead on average derivative effects, which are scalar estimands related to infinitesimal shift interventions requiring only local overlap assumptions. Average ...
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作者：Zeng, Yiran; Zimmerman, Dale L.
作者单位：University of Iowa
摘要：We introduce a new type of test for complete spatial randomness that applies to mapped point patterns in a rectangle or a cube of any dimension. This is the first test of its kind to be based on characteristic functions and utilizes a weighted L-2 distance between the empirical and uniform characteristic functions. The test shows surprising connections with Ripley's K-function and Zimmerman's omega & strns;(2) statistic. It is also simple to calculate and does not require adjusting for edge ef...
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作者：Gao, Chenyin; Yang, Shu; Shan, Mingyang; Ye, Wenyu; Lipkovich, Ilya; Faries, Douglas
作者单位：North Carolina State University; Eli Lilly; Lilly Research Laboratories
摘要：In recent years, real-world external controls have grown in popularity as a tool to empower randomized placebo-controlled trials, particularly in rare diseases or cases where balanced randomization is unethical or impractical. However, as external controls are not always comparable to the trials, direct borrowing without scrutiny may heavily bias the treatment effect estimator. Our paper proposes a data-adaptive integrative framework capable of preventing unknown biases of the external control...
