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用主分层评估部分受控的纵向处理：针具交换项目应用AI 解读

We consider studies for evaluating the short-term effect of a treatment of interest on a time-to-event outcome. The studies we consider are only partially controlled in the following sense: (1) Subjects' exposure to the treatment of interest can vary over time, but this exposure is not directly controlled by the study; (2) subjects' follow-up time is not directly controlled by the study; and (3) the study directly controls another factor that can affect subjects' exposure to…

依赖随机测度的 ANOVA 模型AI 解读

We consider dependent nonparametric models for related random probability distributions. For example, the random distributions might be indexed by a categorical covariate indicating the treatment levels in a clinical trial and might represent random effects distributions under the respective treatment combinations. We propose a model that describes dependence across random distributions in an analysis of variance (ANOVA)-type fashion. We define a probability model in such a…

二元现状数据的独立性检验AI 解读

This article develops a nonparametric procedure for testing marginal independence based on bivariate current status data. Asymptotic properties of the proposed tests are derived, and their finite-sample performance is studied via simulations. The method is applied to analyze data from a community-based study of cardiovascular epidemiology in Taiwan.

用于多维疾病分类流行病学研究的两阶段回归模型AI 解读

Polytomous logistic regression is commonly used to analyze epidemiological data with disease subtype information. In this approach effects of exposures on different disease subtypes are studied through separate exposure odds ratios comparing different case groups to the common control group. This article considers the situation where disease subtypes can be defined using multiple characteristics of a disease. For efficient analysis of such data, a two-stage modeling approach…

期望值变化的非平稳空间数据：样本均值方差的子抽样估计AI 解读

Subsampling and block resampling methods have been suggested in the literature to nonparametrically estimate the variance of statistics computed from spatial data. Usually stationary data are required. However, in empirical applications, the assumption of stationarity often must be rejected. This article proposes nonparametric methods to estimate the variance of (functions of) sample means based on nonstationary spatial data using subsampling. We assume that data are…

用半参数惩罚样条估计公司债利率期限结构AI 解读

This article provides a new methodology for estimating the term structure of corporate debt using a semiparametric penalized spline model. The method is applied to a case study of AT&T bonds. Typically, very few data are available on individual corporate bond prices, too little to find a nonparametric estimate of term structure from these bonds alone. This problem is solved by “borrowing strength” from Treasury bond data. More specifically, we combine a nonparametric model…

模型化地统计中的不一致估计与渐近等价插值AI 解读

It is shown that in model-based geostatistics, not all parameters in the Matérn class can be estimated consistently if data are observed in an increasing density in a fixed domain, regardless of the estimation methods used. Nevertheless, one quantity can be estimated consistently by the maximum likelihood method, and this quantity is more important to spatial interpolation. The results are established by using the properties of equivalence and orthogonality of probability…

多元 Student t 模型中 van Dyk–Meng 算法的几何遍历性AI 解读

Let π denote the posterior distribution that results when a random sample of size n from a d-dimensional location-scale Student's t distribution (with ν degrees of freedom) is combined with the standard noninformative prior. van Dyk and Meng developed an efficient Markov chain Monte Carlo (MCMC) algorithm for sampling from π and provided considerable empirical evidence to suggest that their algorithm converges to stationarity much faster than the standard data augmentation…

模型设定错误的 IOS 检验AI 解读

A new test of model misspecification is proposed, based on the ratio of in-sample and out-of-sample likelihoods. The test is broadly applicable and, in simple problems, approximates well-known, intuitive methods. Using jackknife influence curve approximations, it is shown that the test statistic can be viewed asymptotically as a multiplicative contrast between two estimates of the information matrix, both of which are consistent under correct model specification. This…

时间序列背景下条件均值差异的检验AI 解读

In this article we study tests for equality of two regression curves when the inputs are driven by a time series. The basic process underlying the test statistics is the empirical process of the time series marked by the difference in the pertaining dependent variables. The main results hold under strict stationarity of the input variables, but no mixing condition or special modeling of the time series will be necessary. A simulation study is reported on, which illustrates…

非线性时间序列的蒙特卡洛平滑AI 解读

We develop methods for performing smoothing computations in general state-space models. The methods rely on a particle representation of the filtering distributions, and their evolution through time using sequential importance sampling and resampling ideas. In particular, novel techniques are presented for generation of sample realizations of historical state sequences. This is carried out in a forward-filtering backward-smoothing procedure that can be viewed as the…

基于似然的条件方差函数局部线性估计AI 解读

We consider estimation of mean and variance functions with kernel-weighted local polynomial fitting in a heteroscedastic nonparametric regression model. Our preferred estimators are based on a localized normal likelihood, using a standard local linear form for estimating the mean and a local log-linear form for estimating the variance. It is important to allow two bandwidths in this problem, separate ones for mean and variance estimation. We provide data-based methods for…

单协变量二元回归的核估计量AI 解读

We present a rather thorough investigation of the use of kernel-based nonparametric estimators of the binary regression function in the case of a single covariate. We consider various versions of Nadaraya–Watson and local linear estimators, some involving a single bandwidth and others involving two bandwidths. The locally linear logistic estimator proves to be a good single-bandwidth estimator, although the basic Nadaraya–Watson estimator also fares quite well. Two-bandwidth…

大规模同时假设检验AI 解读

Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties for the statistician, but also opens new opportunities. In particular, it allows empirical estimation of an appropriate null hypothesis. The empirical null may be considerably more dispersed than the usual theoretical null distribution that would be used for any one case…

社区供水系统中污染物共同出现的分析AI 解读

The current framework for U.S. Environmental Protection Agency regulation of water quality in community drinking water supplies produces sequential rules for either single contaminants or small groups of similar contaminants. For both substantive and pragmatic reasons, some water industry experts have advocated the development of a more holistic regulatory process in which rules are promulgated less frequently but for larger contaminant classes. Such a framework would…

蒽环类药物治疗后 ACE 抑制剂试验中不完全依从下的随机化推断AI 解读

Anthracyclines are quite effective at curing certain cancers of childhood, but they may damage the heart. The ACE-Inhibitor After Anthracycline (AAA) study compared enalapril to placebo in a randomized trial in an effort to determine whether treatment with enalapril would preserve or improve cardiac function among children previously treated with anthracylines. As is true in many clinical trials, patient compliance with the study protocol was imperfect; some children took…

A systems cointegration rank test is proposed that is applicable for vector autoregressive (VAR) processes with a structural shift at unknown time. The structural shift is modeled as a simple shift in the level of the process. It is proposed to estimate the break date first on the basis of a full unrestricted VAR model. Two alternative estimators are considered and their asymptotic properties are derived. In the next step the deterministic part of the process including the…

We establish consistency and asymptotic normality of the quasi-maximum likelihood estimator in the linear ARCH model. Contrary to the existing literature, we allow the parameters to be in the region where no stationary version of the process exists. This implies that the estimator is always asymptotically normal.

辍学者会因辍学受损吗？广义选择模型中的结果增益估计与预测AI 解读

Abstract In this paper we describe methods for predicting distributions of outcome gains in the framework of a latent variable selection model. We describe such procedures for Student‐ t selection models and a finite mixture of Gaussian selection models. Importantly, our algorithms for fitting these models are simple to implement in practice, and also permit learning to take place about the non‐identified cross‐regime correlation parameter. Using data from High School and…

尼日利亚母乳喂养启动时间的贝叶斯地理加性建模AI 解读

Abstract A study into the geographical variability of timing of initial child breastfeeding after birth was carried out with the data set from the 1999 Nigeria Demographic and Health Survey. The effect of the metrical covariate of the mother's age at birth was assumed to be nonlinear and estimated nonparametrically. Other categorical covariates are estimated in the usual parametric form. Within a Bayesian context, appropriate priors are assigned for the geographical…

更高功效的面板单位根检验及其实际汇率均值回复应用AI 解读

Abstract Unit root tests, seeking mean or trend reversion, are frequently applied to panel data. We show that more powerful variants of commonly applied tests are readily available. Moreover, power gains persist when the modifications are applied to bootstrap procedures that may be employed when cross‐correlation of a rather general sort among individual panel members is suspected. Copyright © 2004 John Wiley & Sons, Ltd.

混合回归模型中的假设检验AI 解读

Summary We establish asymptotic theory for both the maximum likelihood and the maximum modified likelihood estimators in mixture regression models. Moreover, under specific and reasonable conditions, we show that the optimal convergence rate of n−1/4 for estimating the mixing distribution is achievable for both the maximum likelihood and the maximum modified likelihood estimators. We also derive the asymptotic distributions of two log-likelihood ratio test statistics for…

Summary Multivariate failure time data arise when data consist of clusters in which the failure times may be dependent. A popular approach to such data is the marginal proportional hazards model with estimation under the working independence assumption. In some contexts, however, it may be more reasonable to use the marginal additive hazards model. We derive asymptotic properties of the Lin and Ying estimators for the marginal additive hazards model for multivariate failure…

稀疏聚类数据的复合条件似然AI 解读

Summary Sparse clustered data arise in finely stratified genetic and epidemiologic studies and pose at least two challenges to inference. First, it is difficult to model and interpret the full joint probability of dependent discrete data, which limits the utility of full likelihood methods. Second, standard methods for clustered data, such as pairwise likelihood and the generalized estimating function approach, are unsuitable when the data are sparse owing to the presence of…