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工具变量与平均处理效应的符号AI 解读

This paper considers identification and inference about the sign of the average effect of a binary endogenous regressor (or treatment) on a binary outcome of interest when a binary instrument is available. In this setting, the average effect of the endogenous regressor on the outcome is sometimes referred to as the average treatment effect (ATE). We consider four different sets of assumptions: instrument exogeneity, instrument exogeneity and monotonicity on the outcome…

基于置换的错误发现比例同时置信界AI 解读

Summary When multiple hypotheses are tested, interest is often in ensuring that the proportion of false discoveries is small with high confidence. In this paper, confidence upper bounds for the false discovery proportion are constructed, which are simultaneous over all rejection cut-offs. In particular, this allows the user to select a set of hypotheses post hoc such that the false discovery proportion lies below some constant with high confidence. Our method uses…

多组大规模多重检验整合分析中的信号分类AI 解读

Summary The integrative analysis of multiple data sets is becoming increasingly important in many fields of research. When the same features are studied in several independent experiments, it can often be useful to analyse jointly the multiple sequences of multiple tests that result. It is frequently necessary to classify each feature into one of several categories, depending on the null and non-null configuration of its corresponding test statistics. The paper studies this…

回归不连续设计中分位数处理效应的稳健一致推断AI 解读

The practical importance of inference with robustness against large bandwidths for causal effects in regression discontinuity and kink designs is widely recognized. Existing robust methods cover many cases, but do not handle uniform inference for CDF and quantile processes in fuzzy designs. In this light, this paper extends the literature by developing a unified framework of inference with robustness against large bandwidths that applies to uniform inference for quantile…

第一价格拍卖中基于 GPV 估计量的推断AI 解读

We consider inference on the probability density of valuations in the first-price sealed-bid auctions model within the independent private value paradigm. We show the asymptotic normality of the two-step nonparametric estimator of Guerre et al. (2000) (GPV), and propose an easily implementable and consistent estimator of the asymptotic variance. We prove the validity of the pointwise percentile bootstrap confidence intervals based on the GPV estimator. Lastly, we use the…

诊断试验网络荟萃分析的贝叶斯层级汇总ROC模型AI 解读

In studies evaluating the accuracy of diagnostic tests, three designs are commonly used, crossover, randomized, and non-comparative. Existing methods for meta-analysis of diagnostic tests mainly consider the simple cases in which the reference test in all or none of the studies can be considered a gold standard test, and in which all studies use either a randomized or non-comparative design. The proliferation of diagnostic instruments and the diversity of study designs…

因子成分与特异成分的经验过程AI 解读

The distributions of the common and idiosyncratic components for an individual variable are important in forecasting and applications. However, they are not identified with low-dimensional observations. Using the recently developed theory for large dimensional approximate factor model for large panel data, the common and idiosyncratic components can be estimated consistently. Based on the estimated common and idiosyncratic components, we construct the empirical processes for…

差异马尔可夫随机场分析及微生物群落网络差异检测AI 解读

Micro-organisms such as bacteria form complex ecological community networks that can be greatly influenced by diet and other environmental factors. Differential analysis of microbial community structures aims to elucidate systematic changes during an adaptive response to changes in environment. In this paper, we propose a flexible Markov random field model for microbial network structure and introduce a hypothesis testing framework for detecting differences between networks,…

广义错误控制下序贯多重检验的渐近最优性理论AI 解读

The sequential multiple testing problem is considered under two generalized error metrics. Under the first one, the probability of at least $k$ mistakes, of any kind, is controlled. Under the second, the probabilities of at least $k_{1}$ false positives and at least $k_{2}$ false negatives are simultaneously controlled. For each formulation, the optimal expected sample size is characterized, to a first-order asymptotic approximation as the error probabilities go to 0, and a…

Wiener 泛函最大值的高斯近似及高频数据应用AI 解读

This paper establishes an upper bound for the Kolmogorov distance between the maximum of a high-dimensional vector of smooth Wiener functionals and the maximum of a Gaussian random vector. As a special case, we show that the maximum of multiple Wiener–Itô integrals with common orders is well approximated by its Gaussian analog in terms of the Kolmogorov distance if their covariance matrices are close to each other and the maximum of the fourth cumulants of the multiple…

高斯有序模型选择中的自助法调参AI 解读

The paper focuses on the problem of model selection in linear Gaussian regression with unknown possibly inhomogeneous noise. For a given family of linear estimators $\{\widetilde{\boldsymbol{{\theta}}}_{m},m\in\mathscr{M}\}$, ordered by their variance, we offer a new “smallest accepted” approach motivated by Lepski’s device and the multiple testing idea. The procedure selects the smallest model which satisfies the acceptance rule based on comparison with all larger models.…

优化的断点回归设计AI 解读

The increasing popularity of regression discontinuity methods for causal inference in observational studies has led to a proliferation of different estimating strategies, most of which involve first fitting nonparametric regression models on both sides of a treatment assignment boundary and then reporting plug-in estimates for the effect of interest. In applications, however, it is often difficult to tune the nonparametric regressions in a way that is well calibrated for the…

癌种特异性发病年龄外显率的贝叶斯半参数估计：Li-Fraumeni综合征应用AI 解读

Penetrance, which plays a key role in genetic research, is defined as the proportion of individuals with the genetic variants (i.e., genotype) that cause a particular trait and who have clinical symptoms of the trait (i.e., phenotype). We propose a Bayesian semiparametric approach to estimate the cancer-specific age-at-onset penetrance in the presence of the competing risk of multiple cancers. We employ a Bayesian semiparametric competing risk model to model the duration…

析因实验中的因果交互作用：联合分析应用AI 解读

We study causal interaction in factorial experiments, in which several factors, each with multiple levels, are randomized to form a large number of possible treatment combinations. Examples of such experiments include conjoint analysis, which is often used by social scientists to analyze multidimensional preferences in a population. To characterize the structure of causal interaction in factorial experiments, we propose a new causal interaction effect, called the average…

基于增量倾向得分干预的非参数因果效应AI 解读

Most work in causal inference considers deterministic interventions that set each unit’s treatment to some fixed value. However, under positivity violations these interventions can lead to nonidentification, inefficiency, and effects with little practical relevance. Further, corresponding effects in longitudinal studies are highly sensitive to the curse of dimensionality, resulting in widespread use of unrealistic parametric models. We propose a novel solution to these…

大规模两样本推断中的协变量辅助排序与筛选AI 解读

Summary Two-sample multiple testing has a wide range of applications. The conventional practice first reduces the original observations to a vector of p-values and then chooses a cut-off to adjust for multiplicity. However, this data reduction step could cause significant loss of information and thus lead to suboptimal testing procedures. We introduce a new framework for two-sample multiple testing by incorporating a carefully constructed auxiliary variable in inference to…

高维回归空间中的多重影响点检测AI 解读

Summary Influence diagnosis is an integrated component of data analysis but has been severely underinvestigated in a high dimensional regression setting. One of the key challenges, even in a fixed dimensional setting, is how to deal with multiple influential points that give rise to masking and swamping effects. The paper proposes a novel group deletion procedure referred to as multiple influential point detection by studying two extreme statistics based on a…

近似稀疏固定效应高维动态面板模型的一致有效推断AI 解读

We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can conduct uniformly valid inference on the parameters of the model and construct a uniformly valid estimator of the asymptotic covariance matrix which is robust to conditional…

《利用隐马尔可夫模型 knockoff 寻找基因》作者回复AI 解读

We are very grateful to the editors for the opportunity to expand and deepen the reflection on the possible advantages of a knockoff approach to genome-wide association studies. The discussants bring up a number of important points, related to either the knockoffs methodology in general or its specific application to genetic studies. In this rejoinder we offer some clarifications, mention relevant recent developments, and highlight a few remaining open problems. The model-X…

有向无环图上控制错误发现率的序贯算法AI 解读

We propose a linear-time, single-pass, top-down algorithm for multiple testing on directed acyclic graphs, where nodes represent hypotheses and edges specify a partial ordering in which the hypotheses must be tested. The procedure is guaranteed to reject a sub-directed acyclic graph with bounded false discovery rate while satisfying the logical constraint that a rejected node’s parents must also be rejected. It is designed for sequential testing settings where the directed…

利用隐马尔可夫模型 knockoff 变量寻找关联基因AI 解读

Modern scientific studies often require the identification of a subset of explanatory variables. Several statistical methods have been developed to automate this task, and the framework of knockoffs has been proposed as a general solution for variable selection under rigorous Type I error control, without relying on strong modelling assumptions. In this paper, we extend the methodology of knockoffs to problems where the distribution of the covariates can be described by a…

结构自适应 Benjamini–Hochberg 多重检验算法AI 解读

Summary In multiple-testing problems, where a large number of hypotheses are tested simultaneously, false discovery rate (FDR) control can be achieved with the well-known Benjamini–Hochberg procedure, which a(0, 1]dapts to the amount of signal in the data, under certain distributional assumptions. Many modifications of this procedure have been proposed to improve power in scenarios where the hypotheses are organized into groups or into a hierarchy, as well as other…

局部自适应置信带AI 解读

We develop honest and locally adaptive confidence bands for probability densities. They provide substantially improved confidence statements in case of inhomogeneous smoothness, and are easily implemented and visualized. The article contributes conceptual work on locally adaptive inference as a straightforward modification of the global setting imposes severe obstacles for statistical purposes. Among others, we introduce a statistical notion of local Hölder regularity and…

高斯向量模型中稀疏度的自适应估计AI 解读

Consider the Gaussian vector model with mean value $\theta$. We study the twin problems of estimating the number $\Vert \theta \Vert_{0}$ of nonzero components of $\theta$ and testing whether $\Vert \theta \Vert_{0}$ is smaller than some value. For testing, we establish the minimax separation distances for this model and introduce a minimax adaptive test. Extensions to the case of unknown variance are also discussed. Rewriting the estimation of $\Vert \theta \Vert_{0}$ as a…