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Meta-Analysis of Migraine Headache Treatments: Combining Information from Heterogeneous Designs

偏头痛治疗的元分析:整合异质研究设计的信息

Migraine headache is a common condition in the United States for which a wide range of drug and nondrug treatments are available. There is wide disagreement about which treatments are most effective; meta-analysis of existing clinical trials can help to bring existing evidence to bear on this question. Conducting a meta-analysis is a challenging statistical problem because of the absence of a uniform accepted definition of headache syndromes, the diversity of treatments, and…

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The Versatility of Function-Indexed Weighted Log-Rank Statistics

函数索引加权对数秩统计量的多适应性

Two-sample weighted log-rank statistics are used in the presence of right censoring to test whether failure times from two populations have different survival distributions. Kosorok has showed that large families of these statistics form stochastic processes indexed by weight functions, and that these function-indexed statistics can be used to construct versatile test procedures simultaneously sensitive to a wide array of both ordered hazards and stochastic ordering…

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Combining the Advantages of One-Sided and Two-Sided Test Procedures for Comparing Several Treatment Effects

比较多个处理效应时结合单侧与双侧检验的优势

We consider the one-way layout for comparing k treatment effects μ i , 1 ≤ i ≤ k. Hayter earlier proposed a one-sided studentized range test (OSRT) for testing the null hypothesis H μO: μ1 = μ2 = ··· = μ k against the simple ordered alternative HA : μ1 ≤ μ2 ≤ ··· ≤ μ k with at least one strict inequality. The OSRT gives a set of simultaneous confidence intervals for all ordered pairwise differences μ j - μ i , i < j. These intervals are one-sided and have infinite upper…

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Data-Driven Rank Tests for Independence

数据驱动的独立性秩检验

We introduce new rank tests for testing independence. The new testing procedures are sensitive not only for grade linear correlation, but also for grade correlations of higher-order polynomials. The number of polynomials involved is determined by the data. Model selection is combined with application of the score test in the selected model. Whereas well-known tests as Spearman's test or Hoeffding's test may completely break down for alternatives that are dependent but have…

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Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models

广义线性模型的可识别性、非正常先验与 Gibbs 抽样

Markov chain Monte Carlo algorithms are widely used in the fitting of generalized linear models (GLMs). Such model fitting is somewhat of an art form, requiring suitable trickery and tuning to obtain results in which one can have confidence. A wide range of practical issues arise. The focus here is on parameter identifiability and posterior propriety. In particular, we clarify that nonidentifiability arises for usual GLMs and discuss its implications for simulation-based…

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On Estimation of Monotone and Concave Frontier Functions

单调凹前沿函数的估计

Abstract When analyzing the productivity of firms, one may want to compare how the firms transform a set of inputs x (typically labor, energy or capital) into an output y (typically a quantity of goods produced). The economic efficiency of a firm is then defined in terms of its ability to operate close to or on the production frontier, the boundary of the production set. The frontier function gives the maximal level of output attainable by a firm for a given combination of…

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High-Breakdown Rank Regression

高崩溃点秩回归

A weighted rank estimate is proposed that has 50% breakdown and is asymptotically normal at rate √n. Based on this theory, inferential procedures, including asymptotic confidence and tests, and diagnostic procedures, such as studentized residuals, are developed. The influence function of the estimate is derived and shown to be continuous and bounded everywhere in (x, Y) space. Examples show that robustness against outlying high-leverage clusters may approach that of the…

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A Class of Locally and Globally Robust Regression Estimates

一类局部与全局稳健的回归估计量

We present a new class of regression estimates called generalized τ estimates. These estimates are defined by minimizing the τ scale of the weighted residuals, with weights that penalize high-leverage observations. Like the τ estimates, the generalized τ estimates utilize for their definition two loss functions, ρ1 and ρ2, which together with the weights can be chosen to achieve simultaneously high breakdown point, finite gross error sensitivity, and high efficiency. We…

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Semiparametric Regression Models for Repeated Events with Random Effects and Measurement Error

含随机效应与测量误差的重复事件半参数回归

Statistical methodology is presented for the regression analysis of multiple events in the presence of random effects and measurement error. Omitted covariates are modeled as random effects. Our approach to parameter estimation and significance testing is to start with a naive model of semiparametric Poisson process regression, and then to adjust for random effects and any possible covariate measurement error. We illustrate the techniques with data from a randomized clinical…

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Prediction of Spatial Cumulative Distribution Functions Using Subsampling

利用子抽样预测空间累积分布函数

The spatial cumulative distribution function (SCDF) is a random function that provides a statistical summary of a random field over a spatial domain of interest. In this article we develop a spatial subsampling method for predicting an SCDF based on observations made on a hexagonal grid, similar to the one used in the Environmental Monitoring and Assessment Program of the U.S. Environmental Protection Agency. We show that under quite general conditions, the proposed…

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A Hierarchical Latent Variable Model for Ordinal Data from a Customer Satisfaction Survey with “No Answer” Responses

含“未回答”响应的顾客满意度有序数据分层潜变量模型

We propose an item response theory model for ordinal customer satisfaction data where the probability of each response is a function of latent person and question parameters and of cutoffs for the ordinal response categories. This structure was incorporated into a Bayesian hierarchical model by Albert and Chib. We extend this formulation by modeling item nonresponse, coded as “no answer” (NA), as due to either lack of a strong opinion or indifference to the entire question.…

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The Future of Ecological Inference Research: A Comment on Freedman et al.

生态推断研究的未来:对 Freedman 等人的评论

I appreciate the editor's invitation to reply to Freedman et al.'s (1998) review of A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data (Princeton University Press.) I welcome this scholarly critique and JASA's decision to publish in this field. Ecological inference is a large and very important area for applications that is especially rich with open statistical questions. I hope this discussion stimulates much new…

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Order Statistic Properties, Random Generation, and Goodness-of-Fit Testing for a Minimal Repair Model

最小修复模型的次序统计性质、随机生成与拟合优度检验

We present properties of statistics arising from the Block, Borges, and Savits age-dependent minimal repair model. These properties are analogous to the order statistic properties in homogeneous Poisson processes. These properties are exploited to obtain an algorithm for generating a realization from the minimal repair model, and for testing hypothesis concerning the initial distribution function or hazard function of the repair model.

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A Class of Locally and Globally Robust Regression Estimates

一类局部与全局稳健的回归估计量

We present a new class of regression estimates called generalized τ estimates. These estimates are defined by minimizing the τ scale of the weighted residuals, with weights that penalize high-leverage observations. Like the τ estimates, the generalized τ estimates utilize for their definition two loss functions, ρ1 and ρ2, which together with the weights can be chosen to achieve simultaneously high breakdown point, finite gross error sensitivity, and high efficiency. We…

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Comparing Predictions and Outcomes: Theory and Application to Income Changes

预测与实现结果的比较:理论及收入变化应用

Household surveys often elicit respondents' intentions or predictions of future outcomes. The survey questions may ask respondents to choose among a selection of (ordered) response categories. If panel data or repeated cross-sections are available, then predictions may be compared with realized outcomes. The categorical nature of the predictions data complicates this comparison, however. Generalizing previous findings on binary intentions data, we derive bounds on features…

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Meta-Analysis of Migraine Headache Treatments: Combining Information from Heterogeneous Designs

偏头痛治疗的元分析:融合异质研究设计的信息

Migraine headache is a common condition in the United States for which a wide range of drug and nondrug treatments are available. There is wide disagreement about which treatments are most effective; meta-analysis of existing clinical trials can help to bring existing evidence to bear on this question. Conducting a meta-analysis is a challenging statistical problem because of the absence of a uniform accepted definition of headache syndromes, the diversity of treatments, and…

AI 解读阅读原文 ↗BibTeX ↓

The Versatility of Function-Indexed Weighted Log-Rank Statistics

函数索引加权对数秩统计量的多用途检验

Two-sample weighted log-rank statistics are used in the presence of right censoring to test whether failure times from two populations have different survival distributions. Kosorok has showed that large families of these statistics form stochastic processes indexed by weight functions, and that these function-indexed statistics can be used to construct versatile test procedures simultaneously sensitive to a wide array of both ordered hazards and stochastic ordering…

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Adjusted Score Tests of Homogeneity for Poisson Processes

泊松过程同质性的调整得分检验

Tests of homogeneity are being increasingly used for the analysis of event time data, but relatively little attention has been paid to their distributional properties in settings with small to moderate sample sizes. Here we consider tests of homogeneity for recurrent event data in which the null model is a Poisson process and the alternative is a mixed Poisson process. We examine score and adjusted score statistics in the context of parametric and semiparametric regression…

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Combining the Advantages of One-Sided and Two-Sided Test Procedures for Comparing Several Treatment Effects

比较多个处理效应时结合单侧与双侧检验的优势

We consider the one-way layout for comparing k treatment effects μ i , 1 ≤ i ≤ k. Hayter earlier proposed a one-sided studentized range test (OSRT) for testing the null hypothesis H μO: μ1 = μ2 = ··· = μ k against the simple ordered alternative HA : μ1 ≤ μ2 ≤ ··· ≤ μ k with at least one strict inequality. The OSRT gives a set of simultaneous confidence intervals for all ordered pairwise differences μ j - μ i , i < j. These intervals are one-sided and have infinite upper…

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Improved Estimators in Nonparametric Regression Problems

非参数回归问题中的改进估计量

Linear estimators of multivariate means are considered. Generalizations of some well-known theorems about admissibility of linear estimators are given. The results then are applied to show that commonly used kernel-type estimators in nonparametric regression problems can be constructively improved in a simple way. An asymptotic result is described that gives a quantitative measure of the maximum improvement to be gained in certain situations. A theoretical bound shows that…

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Semiparametric Inference in the Proportional Odds Regression Model

比例优势回归模型的半参数推断

For fitting the proportional odds regression model with right-censored survival times, we introduce some weighted empirical odds functions. These functions are solutions of some self-consistency equations and have a nice martingale representation. From these functions, several classes of new regression estimators, such as the pseudo–maximum likelihood estimator, martingale residual-based estimators, and minimum distance estimators, are derived. These estimators have…

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Semiparametric Regression Models for Repeated Events with Random Effects and Measurement Error

含随机效应与测量误差的重复事件半参数回归模型

Statistical methodology is presented for the regression analysis of multiple events in the presence of random effects and measurement error. Omitted covariates are modeled as random effects. Our approach to parameter estimation and significance testing is to start with a naive model of semiparametric Poisson process regression, and then to adjust for random effects and any possible covariate measurement error. We illustrate the techniques with data from a randomized clinical…

AI 解读阅读原文 ↗BibTeX ↓