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A test of missing completely at random for generalised estimating equations with missing data

缺失数据广义估计方程中的完全随机缺失检验

We consider inference from generalised estimating equations when data are incomplete. A test for missing completely at random is proposed to help decide whether or not we should adjust estimating equations to correct the possible bias introduced by a missing-data mechanism that is not missing completely at random. Likelihood ratio tests have been introduced to test the missing completely at random hypothesis (Fuchs, 1982; Little, 1988). For the estimating equation setting,…

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Treatment Effects in a Logistic Model Involving the Box-Cox Transformation

含 Box–Cox 变换的 Logistic 模型中的处理效应

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…

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Methods for Estimating a Conditional Distribution Function

条件分布函数的估计方法

Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation. It produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1. The second method involves an adjusted form of the…

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Censored Median Regression Using Weighted Empirical Survival and Hazard Functions

基于加权经验生存函数与风险函数的删失中位数回归

For median regression models that regress the median of the survival time or a transform thereof on the covariates, some semi-parametric estimators that include the intercept component are introduced when the survival time may be censored. These new median regression estimators do not require estimating the censoring distributions. They can be viewed as an extension of the sample median to the censored regression model. These estimators are based on some weighted empirical…

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Comparing Predictions and Outcomes: Theory and Application to Income Changes

比较预期与实现结果: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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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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The Influence of Social Programs in Source Countries on Various Classes of U.S. Immigration

来源国社会项目对不同类别赴美移民的影响

"This article uses a unique set of pooled cross-sectional and time series data to examine the annual rate of U.S. immigration during 1972-1991 from 60 source countries. One distinguishing feature of the article is that it breaks out and cross-classifies various classes of immigrants--numerically limited versus numerically exempt and new immigrant versus adjustment of status. A second distinguishing feature is that it utilizes a unique vector of variables relating to the…

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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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Hierarchical Generalized Linear Models in the Analysis of Variations in Health Care Utilization

医疗服务利用差异分析中的层级广义线性模型

In recent years many studies have reported large differences in the use of medical treatments and procedures across geographic regions, hospitals, and individual health care providers. Beyond reporting on the extent of observed variations, these studies examine the role of contributing factors including patient, regional, and provider characteristics. In addition, they may assess the relation between health care processes and outcomes, such as patient mortality, morbidity,…

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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…

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High Wage Workers and High Wage Firms

高工资劳动者与高工资企业

Using a longitudinal sample of one million French workers and 500,000 employing firms, the authors decompose real total annual compensation per worker into components: observable employee characteristics, personal heterogeneity, firm heterogeneity, and residual. Unobserved personal heterogeneity is a very important source of wage variation. Unobserved firm heterogeneity, while important, is not as important as person effects. Enterprises that hire high-wage workers are more…

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SEMIPARAMETRIC ESTIMATION OF A LOCATION PARAMETER IN THE BINARY CHOICE MODEL

二元选择模型中位置参数的半参数估计

This paper considers the estimation of a location parameter in the binary choice model with some weak distributional assumptions imposed on the error term in the latent regression model. Two estimators are proposed here, both of which are two-step estimators; in the first step, the slope parameters are consistently estimated by existing methods; in the second step, the location parameter is consistently estimated based on a moment condition. The estimators are shown to be…

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Multichoice Logit: Modeling Incomplete Preference Rankings of Classical Concerts

多选择 Logit:古典音乐会不完整偏好排序的建模

In this article we develop an econometric model to analyze data on incomplete information on preferences. The available information consists of groups of alternatives that are preferred to other groups of alternatives. Only for the most preferred group is a full ranking observed. The resulting model is estimated on data concerning preferences on classical concerts.

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Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data

面板数据的对称归一化工具变量估计

The authors discuss the estimation of linear panel-data models with sequential moment restrictions using symmetrically normalized generalized method of moments (SNM) estimators and limited information maximum likelihood (LIML) analogues. These estimators are asymptotically equivalent to standard generalized method of moments (GMM) estimators but are invariant to normalization and tend to have a smaller finite-sample bias, especially when the instruments are poor. The authors…

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Multichoice Logit: Modeling Incomplete Preference Rankings of Classical Concerts

多选择 Logit:古典音乐会不完整偏好排序建模

Hans van Ophem, Piet Stam, Bernard van Praag, Multichoice Logit: Modeling Incomplete Preference Rankings of Classical Concerts, Journal of Business & Economic Statistics, Vol. 17, No. 1 (Jan., 1999), pp. 117-128

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Small sample properties of LIML and jackknife IV estimators: experiments with weak instruments

弱工具变量下LIML与刀切工具变量估计量的小样本性质

Using Monte Carlo simulations we study the small sample performance of the traditional TSLS, the LIML and four new jackknife IV estimators when the instruments are weak. We find that the new estimators and LIML have a smaller bias but a larger variance than the TSLS. In terms of root mean square error, neither LIML nor the new estimators perform uniformly better than the TSLS. The main conclusion from the simulations and an empirical application on labour supply functions is…

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Dual and simultaneous sensitivity analysis for matched pairs

匹配对研究的对偶与同时敏感性分析

When a study shows an association between a treatment and a response, before concluding that there is a causal relationship it is useful to assess whether or not an unobserved variable, U, might explain the observed association. Sensitivity analysis clarifies the properties U must have in terms of its relationship to the response and its imbalance in the groups being compared. A substantial literature has investigated the imbalance or association between U and group…

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Spatial adaption for predicting random functions

We study integration and reconstruction of Gaussian random functions with inhomogeneous local smoothness. A single realization may only be observed at a finite sampling design and the correct local smoothness is unknown. We construct adaptive two-stage designs that lead to asymptotically optimal methods. We show that every nonadaptive design is less efficient.

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Nonparametric Regression Analysis of Longitudinal Data

纵向数据的非参数回归分析

Nonparametric methods are developed for estimating the dose effect when a response consists of correlated observations over time measured in a dose–response experiment. The methods can also be applied to data collected from a completely randomized design experiment. Methods are developed for the detection and description of the effects of dose, time, and their interaction. The methods allow for individual variation in the timing and number of observations. A generalization…

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Semiparametric Regression for Repeated Outcomes with Nonignorable Nonresponse

非可忽略无应答下重复结局的半参数回归

We consider inference about the parameter β* indexing the conditional mean of a vector of correlated outcomes given a vector of explanatory variables when some of the outcomes are missing in a subsample of the study and the probability of response depends on both observed and unobserved data values; that is, nonresponse is nonignorable. We propose a class of augmented inverse probability of response weighted estimators that are consistent and asymptotically normal (CAN) for…

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