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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…

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…

非比例风险下的贝叶斯生存分析AI 解读

Both pravastatin and aspirin are approved by the U.S. Food and Drug Administration (FDA) for secondary prevention of cardiovascular events. This article describes statistical analyses used for a successful submission to the FDA that contends that copackaging pravastatin and aspirin provides a health benefit. From the efficacy perspective this is taken to mean that the combination is more effective than either agent considered alone. We present three Bayesian hierarchical…

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…

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…

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of firm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the…

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…

惩罚三角网模型：二维平滑的全变差正则化AI 解读

Summary Hansen, Kooperberg and Sardy introduced a family of continuous, piecewise linear functions defined over adaptively selected triangulations of the plane as a general approach to statistical modelling of bivariate densities and regression and hazard functions. These triograms enjoy a natural affine equivariance that offers distinct advantages over competing tensor product methods that are more commonly used in statistical applications. Triograms employ basis functions…

广义 Bradley–Terry 模型的 MM 算法AI 解读

The Bradley-Terry model for paired comparisons is a simple and much-studied means to describe the probabilities of the possible outcomes when individuals are judged against one another in pairs. Among the many studies of the model in the past 75 years, numerous authors have generalized it in several directions, sometimes providing iterative algorithms for obtaining maximum likelihood estimates for the generalizations. Building on a theory of algorithms known by the initials…

利用教育回报估计教育借贷约束AI 解读

This paper measures the importance of borrowing constraints on education decisions. Empirical identification of borrowing constraints is secured by the economic prediction that opportunity costs and direct costs of schooling affect borrowing-constrained and unconstrained persons differently. Direct costs need to be financed during school and impose a larger burden on credit-constrained students. By contrast, gross forgone earnings do not have to be financed. We explore the…

补救教育与学生成绩：一项断点回归分析AI 解读

As standards and accountability have become increasingly prominent features of the educational landscape, educators have relied more on remedial programs such as summer school and grade retention to help low-achieving students meet minimum academic standards. Yet the evidence on the effectiveness of such programs is mixed, and prior research suffers from selection bias. However, recent school reform efforts in Chicago provide an opportunity to examine the causal impact of…

实验是唯一选择吗？辍学预防项目的评估AI 解读

By comparing experimental and propensity-score impact estimates of dropout prevention programs, we examine whether propensity-score methods produce unbiased estimates of program impacts. We find no consistent evidence that such methods replicate experimental impacts in our setting. This finding holds even when the data available for matching are extensive. Our findings suggest that evaluators who plan to use nonexperimental methods, such as propensity-score matching, need to…

参与时长不同时的学前项目评估：一种非参数方法AI 解读

Nonexperimental data are used to evaluate impacts of a Bolivian preschool program on cognitive, psychosocial, and anthropometric outcomes. Impacts are shown to be highly dependent on age and exposure duration. To minimize the effect of distributional assumptions, program impacts are estimated as nonparametric functions of age and duration. A generalized matching estimator is developed and used to control for nonrandom selectivity into the program and into exposure durations.…

用匹配估计处理效应：数据要求、匹配度量与蒙特卡洛证据AI 解读

We compare propensity-score matching methods with covariatematching estimators. We first discuss the data requirements of propensity-score matching estimators and covariate matching estimators. Then we propose two new matching metrics incorporating the treatment outcome information and participation indicator information, and discuss the motivations of different metrics. Next we study the small-sample properties of propensity-score matching versus covariate matching…

倾向得分方法能否复现强制福利就业项目随机评估的发现？AI 解读

This paper assesses nonexperimental estimators using results from a six-state random assignment study of mandatory welfare-to-work programs. The assessment addresses two questions: which nonexperimental methods provide the most accurate estimates; and do the best methods work well enough to replace random assignment? Three tentative conclusions emerge. Nonexperimental bias was larger in the medium run than in the short run. In-state comparison groups produced less average…

The finite-sample properties of matching and weighting estimators, often used for estimating average treatment effects, are analyzed. Potential and feasible precision gains relative to pair matching are examined. Local linear matching (with and without trimming), k-nearest-neighbor matching, and particularly the weighting estimators performed worst. Ridge matching, on the other hand, leads to an approximately 25% smaller MSE than does pair matching. In addition, ridge…

何时应控制协变量？处理效应估计的面板式渐近分析AI 解读

The problem of when to control for continuous or high-dimensional discrete covariate vectors arises in both experimental and observational studies. Large-cell asymptotic arguments suggest that full control for covariates or stratification variables is always efficient, even if treatment is assigned independently of covariates or strata. Here, we approximate the behavior of different estimators using a panel-data-type asymptotic sequence with fixed cell sizes and the number…

使用匹配、工具变量与控制函数估计经济选择模型AI 解读

This paper investigates four topics. (1) It examines the different roles played by the propensity score (the probability of selection into treatment) in matching, instrumental variable, and control function methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It characterizes the sensitivity of matching to the choice of conditioning variables and demonstrates the greater robustness of control function methods to misspecification…

Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogeneity, unconfoundedness, or selection on observables. The implication of these assumptions is that systematic (for example, average or distributional) differences in outcomes…

03.1.1 利用完全数据似然推导有序 Probit 与 Logit 观测信息矩阵：解答AI 解读

Deriving the observed information matrix in ordered probit and logit models using the complete-data likelihood function—solution.

04.1.1 基于固定效应与误差成分两阶段最小二乘差异的 Hausman 检验AI 解读

A Hausman test based on the difference between fixed effects two-stage least squares and error components two-stage least squares.

多工具变量下的随机效应估计量AI 解读

In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the endogenous regressor. Our proposed estimator puts a random coefficients structure on the relation between the endogenous regressor and the instruments. The variance of the random…

GMM 与广义经验似然估计量的高阶性质AI 解读

In an effort to improve the small sample properties of generalized method of mo-ments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilt-ing estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find…