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有序纵向调查数据分析：广义估计方程方法AI 解读

Longitudinal survey data may comprise ordinal polytomous repeated observations and a set of multidimensional covariates for a large number of individuals. One of the main goals of the longitudinal survey is then to describe the marginal expectation of the ordinal polytomous outcome variable as a function of the covariates while accounting for the structural as well as longitudinal correlations. The structural correlations come from the polytomous nature of the response…

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家庭内肺炎链球菌携带传播：二元纵向数据的潜在马尔可夫过程模型AI 解读

We present a Bayesian data augmentation model to estimate acquisition and clearance rates of carriage of Streptococcus pneumoniae (Pnc) bacteria. The panel observation data comprise 10 measurements of Pnc carriage (carrier/noncarrier of the bacteria) in all members of 97 families with young children over a period of 2 years. Using natural conditional independence assumptions, a transmission model is constructed for the unobserved dependent binary processes of the augmented…

预防 HIV-1 母婴垂直传播的随机试验分析AI 解读

We analyze data from a randomized trial of breastfeeding versus formula feeding in HIV-1-infected mothers and their infants. Estimates of infant HIV-1-free survival and the timing of vertical transmission of HIV-1 are complicated by the fact that the infants' HIV-1 status at death may be unknown, the time of HIV-1 infection may be interval censored, and the tests used to detect HIV-1 infection in the infants may be less than 100% sensitive or specific. To address these…

使用多样本广义 L 统计量稳健分析交叉设计AI 解读

In a crossover study, some or all subjects receive more than one treatment sequentially. Using a clinical example as motivation, we develop multisample generalized L-statistics (GL-statistics) to estimate and test for treatment effects in crossovers when the distribution of the response data deviates from normality. The basic idea is to adapt simple L-statistics, such as the trimmed mean and median, to data with dependencies. GL-statistics may be applied to crossovers with…

预防 HIV-1 母婴传播随机试验的分析AI 解读

We analyze data from a randomized trial of breastfeeding versus formula feeding in HIV-1-infected mothers and their infants. Estimates of infant HIV-1-free survival and the timing of vertical transmission of HIV-1 are complicated by the fact that the infants' HIV-1 status at death may be unknown, the time of HIV-1 infection may be interval censored, and the tests used to detect HIV-1 infection in the infants may be less than 100% sensitive or specific. To address these…

混合线性模型的小样本推断改进：Bartlett 校正与调整似然AI 解读

Summary The mixed linear model is a popular method for analysing unbalanced repeated measurement data. The classical statistical tests for parameters in this model are based on asymptotic theory that is unreliable in the small samples that are often encountered in practice. For testing a given fixed effect parameter with a small sample, we develop and investigate refined likelihood ratio (LR) tests. The refinements considered are the Bartlett correction and use of the…

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用间接推断解决初始条件问题AI 解读

In this paper, we study the initial-conditions problem, a complication associated with left-censored or interrupted spells in the econometric analysis of labor market transitions. In the presence of unobserved individual-specific heterogeneity, no consistent estimators have been previously constructed. This paper proposes such an estimator using indirect inference (II). The II procedure simulates the structural model and "matches" the simulated data with the actual data via…

随机占优及贫困与不平等测度的统计推断AI 解读

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare, and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality, or social welfare is greater in one distribution than in another for general classes of indices and…

最大最小期望效用的计量经济学应用AI 解读

Abstract Gilboa and Schmeidler (1989) develop a set of axioms for decision making under uncertainty. The axioms imply a utility function and a set of distributions such that the preference ordering is obtained by calculating expected utility with respect to each distribution in the set, and then taking the minimum of expected utility over the set. In a portfolio choice problem, the distributions are joint distributions for the data that will be available when the choice is…

营销组合变量具有不同长期与短期效应的动态多项 Probit 品牌选择模型AI 解读

Abstract In this paper we propose a dynamic multinomial probit model in order to estimate the long‐run and short‐ run effects of marketing mix variables on brand choice. The latent variables, which contain the unobserved perceived utilities, follow a first‐order vector error correction autoregressive process of order 1 with current and lagged explanatory variables. The unrestricted autoregressive parameter matrix concerns the intertemporal correlation in perceived utilities…

动态离散选择模型中的序列相关变量AI 解读

Abstract This paper discusses the problems that are encountered when dynamic, discrete choice models are specified with continuous, serially correlated state variables. A variety of approximation methods that can deal with these problems is examined, and an empirical example that allows continuous variables to be serially correlated is presented. Copyright © 2000 John Wiley & Sons, Ltd.

加拿大与美国工资分布差异：含协变量的灵活分布函数估计AI 解读

We construct a tractable, flexible-functional-form estimator of cumulative distribution functions for non-negative random variables which admits large numbers of covariates. The estimator adopts and extends techniques from the spell-duration literature for estimating hazard functions to distribution functions for wages, earnings, and income. We apply these methods to investigate sources of wage inequality for full-time male workers between Canada and the United States,…

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不平等排序、归一化随机占优与统计推断AI 解读

This article derives large-sample properties and provides asymptotically distribution-free statistical inference procedures for an alternative approach to inequality orderings—normalized stochastic dominance (NSD). NSD is a straightforward extension of standard dominance techniques. As such, it can be generalized to higher orders of dominance, thereby providing a more powerful technique for ranking distributions. We illustrate the NSD method by applying it to Current…

随机试验中的中位数处理效应AI 解读

Summary For two response variables y t and y c corresponding to two treatments for two policies) T and C, we wish to learn about quantiles of y t−y c from the marginal quantiles of y t and y c; only one of y t and y c is observed for an individual. We find that, in general, this is difficult for quantiles other than the median unless strong assumptions are imposed on how y t is related to y c. For the median, we present conditions under which the sign of the median treatment…

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…

利用期望估计方程处理协变量测量误差AI 解读

Summary Estimating equations which are not necessarily likelihood-based score equations are becoming increasingly popular for estimating regression model parameters. This paper is concerned with estimation based on general estimating equations when true covariate data are missing for all the study subjects, but surrogate or mismeasured covariates are available instead. The method is motivated by the covariate measurement error problem in marginal or partly conditional…

偏倚函数未知时基于有偏样本的非参数密度估计AI 解读

We present a kernel estimator for the density of a variable when sampling probabilities depend on that variable. Both the density and sampling bias weight functions are unknown and are estimated nonparametrically. To achieve this, the method requires that two independent samples be taken from a fixed finite population. An estimator of population size follows simply from our density estimator. Asymptotic bias and standard errors for these estimators are provided, and the…

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…

非平稳二元选择AI 解读

This paper develops an asymptotic theory for time series binary choice models with nonstationary explanatory variables generated as integrated processes. Both logit and probit models are covered. The maximum likelihood (ML) estimator is consistent but a new phenomenon arises in its limit distribution theory. The estimator consists of a mixture of two components, one of which is parallel to and the other orthogonal to the direction of the true parameter vector, with the…