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敏感性分析中的渐近可分性AI 解读

Summary In an observational study in which each treated subject is matched to several untreated controls by using observed pretreatment covariates, a sensitivity analysis asks how hidden biases due to unobserved covariates might alter the conclusions. The bounds required for a sensitivity analysis are the solution to an optimization problem. In general, this optimization problem is not separable, in the sense that one cannot find the needed optimum by performing a separate…

部分数据缺失时倾向得分的估计与使用AI 解读

Investigators in observational studies have no control over treatment assignment. As a result, large differences can exist between the treatment and control groups on observed covariates, which can lead to badly biased estimates of treatment effects. Propensity score methods are an increasingly popular method for balancing the distribution of the covariates in the two groups to reduce this bias; for example, using matching or subclassification, sometimes in combination with…

单调工具变量：教育回报的应用AI 解读

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects.Yet the credibility of IV assumptions is often a matter of considerable disagreement.There is therefore good reason to consider weaker but more credible assumptions.To this end, we introduce monotone instrumental variable (MIV) assumptions and the important special case of monotone treatment selection (MTS).We study the identifying power of MIV…

联立方程模型中工具变量估计量的解释：鱼类需求的应用AI 解读

In markets where prices are determined by the intersection of supply and demand curves, standard identification results require the presence of instruments that shift one curve but not the other. These results are typically presented in the context of linear models with fixed coefficients and additive residuals. The first contribution of this paper is an investigation of the consequences of relaxing both the linearity and the additivity assumption for the interpretation of…

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不依赖反事实的因果推断AI 解读

A popular approach to the framing and answering of causal questions relies on the idea of counterfactuals: Outcomes that would have been observed had the world developed differently; for example, if the patient had received a different treatment. By definition, one can never observe such quantities, nor assess empirically the validity of any modeling assumptions made about them, even though one's conclusions may be sensitive to these assumptions. Here I argue that for making…

多维纵向数据：从连续、离散或事件时间响应估计治疗效应AI 解读

Multidimensional data arise when a number of different response variables are required to measure the outcome of interest. Examples of such outcomes include quality of life, cognitive ability, and health status. The goal of this article is to develop a methodology to estimate a treatment effect from multidimensional data that have been collected longitudinally using continuous, discrete, or time-to-event responses or a mixture of these types of responses. A transformation of…

两样本多状态加速停留时间模型AI 解读

Many medical studies involve observations of patients experiencing multiple consecutive states during their follow-up. Since treatments may have differential effects on these states, comparison is of interest with respect to individual sojourn times. In this article I generalize the univariate accelerated failure time model for multistate processes and model the treatment effects as state-specific time scale changes. I propose a two-sample inference procedure that…

结合倾向得分匹配与预后协变量的额外调整AI 解读

Propensity score matching refers to a class of multivariate methods used in comparative studies to construct treated and matched control samples that have similar distributions on many covariates. This matching is the observational study analog of randomization in ideal experiments, but is far less complete as it can only balance the distribution of observed covariates, whereas randomization balances the distribution of all covariates, both observed and unobserved. An…

两样本多状态加速停留时间模型AI 解读

Many medical studies involve observations of patients experiencing multiple consecutive states during their follow-up. Since treatments may have differential effects on these states, comparison is of interest with respect to individual sojourn times. In this article I generalize the univariate accelerated failure time model for multistate processes and model the treatment effects as state-specific time scale changes. I propose a two-sample inference procedure that…

协变量和结局缺失的随机实验非参数分析AI 解读

Analysis of randomized experiments with missing covariate and outcome data is problematic, because the population parameters of interest are not identified unless one makes untestable assumptions about the distribution of the missing data. This article shows how population parameters can be bounded without making untestable distributional assumptions. Bounds are also derived under the assumption that covariate data are missing completely at random. In each case the bounds…

含缺失二元结局、辅助变量与全有或全无依从性的随机癌症预防试验分析AI 解读

The Prostate Cancer Prevention Trial is a randomized chemoprevention trial designed to compare the effect of daily finasteride versus placebo on prostate cancer determined by biopsy. Investigators have scheduled a biopsy at the end of the trial in 7 years or following a positive prostate-specific antigen (PSA) on annual screening. The analysis will need to adjust for two likely complications. First, some subjects will not receive a biopsy, depending in part on whether or not…

结局缺失、辅助变量及全有或全无依从下的随机癌症预防试验分析AI 解读

The Prostate Cancer Prevention Trial is a randomized chemoprevention trial designed to compare the effect of daily finasteride versus placebo on prostate cancer determined by biopsy. Investigators have scheduled a biopsy at the end of the trial in 7 years or following a positive prostate-specific antigen (PSA) on annual screening. The analysis will need to adjust for two likely complications. First, some subjects will not receive a biopsy, depending in part on whether or not…

非实验研究中的因果效应：重新评估培训项目评价AI 解读

This article uses propensity score methods to estimate the treatment impact of the National Supported Work (NSW) Demonstration, a labor training program, on postintervention earnings. We use data from Lalonde's evaluation of nonexperimental methods that combine the treated units from a randomized evaluation of the NSW with nonexperimental comparison units drawn from survey datasets. We apply propensity score methods to this composite dataset and demonstrate that, relative to…

用广义断点回归设计评估加利福尼亚州囚犯分类系统AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

用广义断点回归设计评估加州囚犯分类制度AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

内生处理效应模型的估计与解释AI 解读

This article examines the relationship between two alternative approaches, instrumental variables and control function procedures, for estimating the impact of endogenous treatment effects. Although it is well known that the two approaches generate comparable estimates, the relationship between the estimators and their accompanying endogeneity tests appears not to be well understood. We show that the two procedures are closely related. We also examine the implications of the…

时变暴露对重复二元结局边际均值的因果效应估计AI 解读

We provide sufficient conditions for estimating from longitudinal data the causal effect of a time-dependent exposure or treatment on the marginal probability of response for a dichotomous outcome. We then show how one can estimate this effect under these conditions using the g-computation algorithm of Robins. We also derive the conditions under which some current approaches to the analysis of longitudinal data, such as the generalized estimating equations (GEE) approach of…

全有或全无处理不依从与后续结果缺失下的意向治疗分析AI 解读

We study the combined impact that all-or-none compliance and subsequent missing outcomes can have on the estimation of the intention-to-treat effect of assignment in randomised studies. In this setting, a standard analysis, which drops subjects with missing outcomes and ignores compliance information, can be biased for the intention-to-treat effect. To address all-or-none compliance that is followed by missing outcomes, we construct a new estimation procedure for the…

含 Box–Cox 变换的 Logistic 模型中的处理效应AI 解读

We consider a logistic model for binary response data that allows the possibility of power transformation of x; that is, log[p/(1 - p)] = α + βx (λ) + γI, where x is a continuous variable, x (λ) is the Box–Cox transformation, and I is a binary variable indicating treatment or group. This model is applicable to observational studies or randomized trials when a treatment effect is investigated after controlling for a confounding variable x. Our focus is on inference concerning…

偏头痛治疗的元分析：整合异质研究设计的信息AI 解读

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…

比较多个处理效应时结合单侧与双侧检验的优势AI 解读

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…

含“未回答”响应的顾客满意度有序数据分层潜变量模型AI 解读

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.…

偏头痛治疗的元分析：融合异质研究设计的信息AI 解读

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…