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信息性观测与删失时间下的纵向数据回归分析AI 解读

Longitudinal data frequently occur in many studies, such as longitudinal follow-up studies. To develop statistical methods and theory for the analysis of these data, independent or noninformative observation and censoring times are typically assumed, which naturally leads to inference procedures conditional on observation and censoring times. But in many situations this may not be true or realistic; that is, longitudinal responses may be correlated with observation times as…

由纵向分类数据估计事件发生时间AI 解读

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing of one point of EDSS (relative progression). Survival methods for time to progression are not adequate for such data since they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated…

随机对照试验中他莫昔芬预防乳腺癌效应的推断AI 解读

The largest randomized, double-blind, placebo-controlled chemoprevention trial, the National Surgical Adjuvant Breast and Bowel Project's Breast Cancer Prevention Trial (NSABP-BCPT), evaluated the efficacy of tamoxifen in the prevention of breast cancer among women at high risk of developing the disease. The trial has reported a reduction of breast cancer incidence for the tamoxifen group. However, the effect of tamoxifen on the time to diagnosis of the disease over the…

拉丁美洲基础设施特许经营：政府主导的重新谈判AI 解读

Abstract This paper analyzes government‐led renegotiations in infrastructure concession contracts in Latin America, based on the same sample used in Guasch, Laffont and Straub (2003) to examine firm‐led renegotiations. After extending the theoretical framework to a multiple‐period context in which both Pareto‐improving and rent‐shifting renegotiations at the initiative of the government can occur, we develop an original instrumental variable strategy to address the issue of…

广告竞争的半结构模型AI 解读

Abstract We propose a semi‐structural discrete‐choice model that can be used to estimate static or dynamic decision rules. It is particularly useful in strategic contexts when games involve a rich set of choices, when private information is correlated, and when one wants to uncover the effect of historic behavior (on, for example, prices, sales, and profits). We apply our discrete‐choice estimator to study decision rules for a dynamic game of price and advertising…

研发合作、补贴与研发绩效：芬兰和德国的经验证据AI 解读

Abstract This study focuses on the impact of innovation policies and R&D collaboration in Germany and Finland. We consider collaboration and subsidies as heterogeneous treatments, and perform an econometric matching to analyze R&D and patent activity at the firm level. In general, we find that collaboration has positive effects. In Germany, subsidies for individual research do neither exhibit a significant impact on R&D nor on patenting, but the innovative performance could…

随机化后事件发生才观测结局时，给定基线协变量的治疗效应半参数估计AI 解读

Summary We consider estimation, from a double-blind randomized trial, of treatment effect within levels of base-line covariates on an outcome that is measured after a post-treatment event E has occurred in the subpopulation 𝒫E,E that would experience event E regardless of treatment. Specifically, we consider estimation of the parameters γ indexing models for the outcome mean conditional on treatment and base-line covariates in the subpopulation 𝒫E,E. Such parameters are…

使用近似工具变量的测量误差建模AI 解读

Summary Consider using regression modelling to relate an exposure (predictor) variable to a disease outcome (response) variable. If the exposure variable is measured with error, but this error is ignored in the analysis, then misleading inferences can result. This problem is well known and has spawned a large literature on methods which adjust for measurement error in predictor variables. One theme is that the requisite assumptions about the nature of the measurement error…

固定效应面板数据模型的稳健估计量AI 解读

The presence of outlying observations in panel data can affect the classical estimates in a dramatic way. Nevertheless, the common practice seems to disregard the problem. The aim of this work is to study robust regression techniques in the fixed effects linear panel data framework. Robustness of the procedures is investigated by means of breakdown point computations and simulation experiments. A distinction between outlying blocks and cells in a panel is made. To show the…

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利用州行政数据衡量项目绩效AI 解读

We use administrative data from Missouri to examine the sensitivity of earnings impact estimates for a job training program based on alternative nonexperimental methods. We consider regression adjustment, Mahalanobis distance matching, and various methods using propensity-score matching, examining both cross-sectional estimates and difference-in-difference estimates. Specification tests suggest that the difference-in-difference estimator may provide a better measure of…

形状不变恩格尔曲线的半非参数工具变量估计AI 解读

This paper studies a shape-invariant Engel curve system with endogenous total expenditure, in which the shape-invariant specification involves a common shift parameter for each demographic group in a pooled system of nonparametric Engel curves. We focus on the identification and estimation of both the nonparametric shapes of the Engel curves and the parametric specification of the demographic scaling parameters. The identification condition relates to the bounded…

迭代估计方程：线性收敛与渐近性质AI 解读

We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the…

含协变量面板计数数据的两种基于似然的半参数估计方法AI 解读

We consider estimation in a particular semiparametric regression model for the mean of a counting process with “panel count” data. The basic model assumption is that the conditional mean function of the counting process is of the form E{ℕ(t)|Z}=exp(β0TZ)Λ0(t) where Z is a vector of covariates and Λ0 is the baseline mean function. The “panel count” observation scheme involves observation of the counting process ℕ for an individual at a random number K of random time points;…

固定效应动态面板离散选择模型的估计AI 解读

In this paper, I consider the estimation of dynamic binary choice panel data models with fixed effects. I use a Modified Maximum Likelihood Estimator (MMLE) that reduces the order of the bias in the Maximum Likelihood Estimator from O(T^(-1)) to O(T^(-2)), without increasing the asymptotic variance. I evaluate its performance in finite samples where T is not large, using Monte Carlo simulations. In Probit and Logit models containing lags of the endogenous variable and…

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动态面板中分数型因变量的估计及其在企业股利政策中的应用AI 解读

Fractional dependent variables and models with state dependence arise in many economic applications; however, estimating models with fractional dependent variables is complicated by the presence of two corner solution outcomes. When coupled with a dynamic panel data setting, estimating quantities of interest can be quite complex or computationally difficult. This article demonstrates a method for estimating fractional response variables, which is easy to implement, and…

存在不依从与对照组接受治疗时比例风险模型中的治疗效应估计AI 解读

Summary Methods for adjusting for non-compliance and contamination, which respect the randomization, are extended from binary outcomes to time-to-event analyses by using a proportional hazards model. A simple non-iterative method is developed when there are no covariates, which is a generalization of the Mantel–Haenszel estimator. More generally, a ‘partial likelihood’ is developed which accommodates covariates under the assumption that they are independent of compliance. A…

纵向数据的函数聚类与子结构识别AI 解读

Summary A functional clustering (FC) method, k-centres FC, for longitudinal data is proposed. The k-centres FC approach accounts for both the means and the modes of variation differentials between clusters by predicting cluster membership with a reclassification step. The cluster membership predictions are based on a non-parametric random-effect model of the truncated Karhunen–Loève expansion, coupled with a non-parametric iterative mean and covariance updating scheme. We…

贝叶斯Probit回归MCMC算法的收敛速度与渐近标准误AI 解读

Summary Consider a probit regression problem in which Y1, …, Yn are independent Bernoulli random variables such that Pr(Yi=1)=Φ(xiTβ) where xi is a p-dimensional vector of known covariates that are associated with Yi, β is a p-dimensional vector of unknown regression coefficients and Φ(·) denotes the standard normal distribution function. We study Markov chain Monte Carlo algorithms for exploring the intractable posterior density that results when the probit regression…

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