Biometrika

最新文章

• Aggregating conformal prediction sets via $ \alpha $-allocation AI翻译
  作者：Xu, Congbin; Yu, Yue; Wang, Zhaojun; Zou, Changliang; Ren, Haojie
  作者单位：Nankai University; Nankai University; Shanghai Jiao Tong University
  摘要：Conformal prediction offers a distribution-free framework for constructing prediction sets with finite-sample coverage. Yet efficiently leveraging multiple nonconformity scores to reduce set sizes remains an open challenge. Instead of selecting a single best score, this work introduces a principled aggregation strategy that intersects multiple conformal prediction sets, with confidence levels allocated optimally to minimize the empirical set size while maintaining asymptotic coverage. Two vari...
• Using negative controls to identify causal effects with invalid instrumental variables AI翻译
  作者：Dukes, O.; Richardson, D. B.; Shahn, Z.; Robins, J. M.; Tchetgen, E. J. Tchetgen
  作者单位：Ghent University; University of California System; University of California Irvine; City University of New York (CUNY) System; Harvard University; Harvard T.H. Chan School of Public Health; University of Pennsylvania
  摘要：Many proposals for the identification of causal effects require an instrumental variable that satisfies strong, untestable unconfoundedness and exclusion restriction assumptions. In this paper, we show how one can potentially identify causal effects under violations of these assumptions by harnessing a negative control population or outcome. This strategy allows one to leverage subpopulations for whom the exposure is degenerate, and requires that the instrument-outcome association satisfies a ...
• Doubly robust estimation under a possibly misspecified marginal structural Cox model AI翻译
  作者：Luo, Jiyu; Rava, Denise; Bradic, Jelena; Xu, Ronghui
  作者单位：University of California System; University of California San Diego; University of California System; University of California San Diego
  摘要：In this article we consider the marginal structural Cox model, which has been widely used to analyse observational studies with survival outcomes. The standard inverse probability weighting method under the model hinges on a propensity score model for the treatment assignment and a censoring model that incorporates both the treatment and the covariates. In such settings model misspecification can often occur, and the Cox regression model's non-collapsibility has historically posed challenges w...
• Sensitivity analysis for observational studies with flexible matched designs AI翻译
  作者：Li, Xinran
  作者单位：University of Chicago
  摘要：Observational studies provide invaluable opportunities to draw causal inference, but they may suffer from biases due to pretreatment differences between treated and control units. Matching is a popular approach to reduce observed covariate imbalance. To tackle unmeasured confounding, a sensitivity analysis is often conducted to investigate how robust a causal conclusion is to the strength of unmeasured confounding. For matched observational studies, Rosenbaum proposed a sensitivity analysis fr...
• Harnessing the collective wisdom: fusion learning using decision sequences from diverse sources AI翻译
  作者：Banerjee, Trambak; Gang, Bowen; He, Jianliang
  作者单位：University of Kansas; Fudan University; Yale University
  摘要：We introduce an integrative ranking and thresholding framework for fusing evidence from multiple testing procedures. The key innovation is a method that transforms binary testing decisions into compound $ e $-values, enabling the combination of findings across diverse data sources or studies. We demonstrate that our new framework ensures overall false discovery rate control, provided that the individual studies maintain their respective false discovery rate levels. The proposed approach is hig...
• Nonparametric inference for balance in signed networks AI翻译
  作者：Chen, Xuyang; Wang, Yinjie; Tang, Weijing
  作者单位：University of Pennsylvania; University of Chicago; Carnegie Mellon University
  摘要：In many real-world networks, relationships often go beyond simple dyadic presence or absence; they can be positive, such as friendship, alliance and mutualism, or negative, characterized by enmity, disputes and competition. To understand the mechanisms of formation of such signed networks, social balance theory sheds light on the dynamics of positive and negative connections. In particular, it characterizes the proverbs 'a friend of my friend is my friend' and 'an enemy of my enemy is my frien...
• Uniform inference in linear mixed models AI翻译
  作者：Ekvall, Karl Oskar; Bottai, Matteo
  作者单位：University of Florida; State University System of Florida; University of Florida; Karolinska Institutet
  摘要：We provide finite-sample distribution approximations that are uniform in the parameter for inference in linear mixed models. The focus is on variances and covariances of random effects in cases where existing theory fails because the covariance matrix is nearly or exactly singular and hence near or at the boundary of the parameter set. Quantitative bounds on the differences between the standard normal density and densities of linear combinations of the score function enable, for example, the a...
• A family of toroidal diffusions with exact likelihood inference AI翻译
  作者：Garcia-Portugues, E.; Sorensen, M.
  作者单位：University of Copenhagen
  摘要：We provide a class of diffusion processes for continuous time-varying multivariate angular data with explicit transition probability densities, enabling exact likelihood inference. The presented diffusions are time reversible and can be constructed for any prespecified stationary distribution on the torus, including highly multimodal mixtures. We give results on asymptotic likelihood theory, allowing one-sample inference and tests of linear hypotheses for $ k $ groups of diffusions, including ...
• Nonparametric efficient estimation of marginal structural models with continuous time-varying treatments AI翻译
  作者：Martin, A.; Santacatterina, M.; Diaz, I
  作者单位：New York University
  摘要：Marginal structural models are a popular method for estimating causal effects in the presence of time-varying exposures. In spite of their popularity, no scalable nonparametric estimator exists for marginal structural models with multi-valued or continuous time-varying treatments. In this paper, we combine flexible, data-adaptive regression methods, including ensemble learning techniques, with recent developments in semiparametric efficiency theory for longitudinal studies to propose such an e...
• Robust universal inference for misspecified models AI翻译
  作者：Park, Beomjo; Balakrishnan, Sivaraman; Wasserman, Larry
  作者单位：Carnegie Mellon University
  摘要：In statistical inference, it is rarely realistic to assume that the hypothesized statistical model is well specified; consequently, it is important to understand the effects of misspecification on inferential procedures. When the hypothesized statistical model is misspecified, the natural target of inference is a projection of the data-generating distribution onto the model. We present a general method for constructing valid confidence sets for such projections, under weak regularity condition...