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连续稀释试验重复二元数据的非参数混合效应模型：艾滋病病毒负荷估计AI 解读

This article develops methods for estimating treatment effects in mixed-effects models using outcome data gathered from serial dilution assays. Our application allows us to estimate the viral burden of HIV infection before and after antiviral treatment from cell dilution assays. This assay is designed to determine the infectious units per patient peripheral blood mononuclear cell (PBMC). The infectious unit is the amount of virus required to produce detectable HIV infection…

多评分者有序数据的贝叶斯分析：自动作文评分应用AI 解读

A framework is proposed for the analysis of ordinal categorical data when ratings from several judges are available. I emphasize the tasks of estimating latent trait characteristics of individual items, regressing these latent traits on observed covariates, and comparing the performance of raters. The model is illustrated in the design and evaluation of an automated essay grader. This grader is based on a regression of variables, obtained from a grammar checker, on essay…

存在不可忽略缺失的纵向有序临床试验依从性数据：贝叶斯 Tobit 建模AI 解读

In the Lung Health Study (LHS), compliance with the use of inhaled medication was assessed at each follow-up visit both by self-report and by weighing the used medication canisters. One or both of these assessments were missing if the participant failed to attend the visit or to return all canisters. Approximately 30% of canister-weight data and 5% to 15% of self-report data were missing at different visits. We use Gibbs sampling with data augmentation and a multivariate…

存在不可忽略缺失的纵向有序临床试验依从性数据：贝叶斯 Tobit 建模AI 解读

In the Lung Health Study (LHS), compliance with the use of inhaled medication was assessed at each follow-up visit both by self-report and by weighing the used medication canisters. One or both of these assessments were missing if the participant failed to attend the visit or to return all canisters. Approximately 30% of canister-weight data and 5% to 15% of self-report data were missing at different visits. We use Gibbs sampling with data augmentation and a multivariate…

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连续稀释试验重复二元数据的非参数混合效应模型：艾滋病病毒负荷估计AI 解读

This article develops methods for estimating treatment effects in mixed-effects models using outcome data gathered from serial dilution assays. Our application allows us to estimate the viral burden of HIV infection before and after antiviral treatment from cell dilution assays. This assay is designed to determine the infectious units per patient peripheral blood mononuclear cell (PBMC). The infectious unit is the amount of virus required to produce detectable HIV infection…

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双层收入前沿模型的面板估计AI 解读

This paper uses panel data to estimate a two-tiered instead of a one-tiered frontier model. The innovation is to develop a two-step maximum likelihood procedure yielding consistent estimates of inefficiency, while at the same time accounting for heterogeneity. The model is applied by estimating a 'two-tiered' earnings function to obtain indices of worker and firm incomplete labour market wage information using panel data from the Panel Study of Income Dynamics (1969-84). The…

REML 估计：渐近行为及相关问题AI 解读

The restricted maximum likelihood (REML) estimates of dispersion parameters (variance components) in a general (non-normal) mixed model are defined as solutions of the REML equations. In this paper, we show the REML estimates are consistent if the model is asymptotically identifiable and infinitely informative under the (location) invariant class, and are asymptotically normal (A.N.) if in addition the model is asymptotically nondegenerate. The result does not require…

跨行业与跨国生产率：时间序列理论与证据AI 解读

The authors examine whether convergence in aggregate productivity is also occurring at the industry level in fourteen OECD countries from 1970 to 1987. Using both cross-section and time-series methods, they find convergence in some sectors, such as services. However, surprisingly, the authors find that convergence does not hold for the manufacturing sector. Decomposing aggregate convergence into industry productivity gains and changing sectoral shares of output, they find…

离散与连续重复测量中随机化后协变量的处理AI 解读

SUMMARY Adjusting for covariates observed post randomization is a difficult issue in randomized clinical trials. One approach is to enter these covariates as time-dependent covariates in a general linear model. However, this approach fails to account for interactions between the primary end point and confounding variable as they evolve over time. In this paper, we adopt the view that, since the confounder is observed following randomization, it should be treated as an…

面板数据回归模型的半参数估计AI 解读

Linear models with error components are widely used to analyse panel data. Some applications of these models require knowledge of the probability densities of the error components. Existing methods handle this requirement by assuming that the densities belong to known parametric families of distributions (typically the normal distribution). This paper shows how to carry out nonparametric estimation of the densities of the error components, thereby avoiding the assumption…

消费者面板数据分析中的交互式图形方法AI 解读

The study of complex market phenomena is often supported by data gathered from panels of customer households. Recent advances in statistical graphics research help analysts do justice to the richness of such data. The authors describe a graphical approach based on the use of simple linked plots in which case identity is preserved. The expressive power of these plots is enhanced by a variety of interactions such as painting and identification. The authors also introduce the…

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持久收入、当期收入与消费：来自两个面板数据集的证据AI 解读

In this paper, the author estimates Euler equations, i.e., the first order conditions of the consumers' maximization problem, using data from two data sets. Consumption data are taken from the Consumer Expenditure Survey. Income data are taken from the Panel Study of Income Dynamics. Since the data for the estimation come from two samples, the author uses a generalization of the instrumental variables estimator: two-sample instrumental variables estimator. She finds evidence…

随机缺失观测下马尔可夫依赖二元序列的经验贝叶斯模型AI 解读

We develop an improved empirical Bayes estimation methodology for the analysis of two-state Markov chains observed from heterogeneous individuals. First, the two transition probabilities corresponding to each chain are assumed to be drawn from a common, bivariate distribution that has beta marginals. Second, randomly missing observations are incorporated into the likelihood for the hyperparameters by efficiently summing over all possible values for the missing observations.…

利用全局优势比分析双变量有序数据AI 解读

A moment method is proposed for regression analysis of bivariate ordered categorical data using the global odds ratio as the measure of association. For modeling the margins, this method utilizes the stochastic ordering implicit in the data. This method allows for covariate effects in modeling the association between responses. An application of the proposed model is illustrated using the ophthalmological data from the Wisconsin Epidemiologic Study of Diabetic Retinopathy…

随机缺失的马尔可夫依赖二元序列的经验贝叶斯模型AI 解读

We develop an improved empirical Bayes estimation methodology for the analysis of two-state Markov chains observed from heterogeneous individuals. First, the two transition probabilities corresponding to each chain are assumed to be drawn from a common, bivariate distribution that has beta marginals. Second, randomly missing observations are incorporated into the likelihood for the hyperparameters by efficiently summing over all possible values for the missing observations.…

多元二元响应的边际回归分析AI 解读

We propose the use of the mean parameter for regression analysis of a multivariate binary response. We model the association using dependence ratios defined in terms of the mean parameter, the components of which are the joint success probabilities of all orders. This permits flexible modelling of higher-order associations, using maximum likelihood estimation. We reanalyse two data sets, one with variable cluster size and the other a longitudinal data set with constant…

存在信息性退出的纵向二元响应回归模型AI 解读

SUMMARY This paper reviews both likelihood-based and non-likelihood (generalized estimating equations) regression models for longitudinal binary responses when there are drop-outs. Throughout, it is assumed that the regression parameters for the marginal expectations of the binary responses are of primary scientific interest. The association or time dependence between the responses is largely regarded as a nuisance characteristic of the data. The performance of the methods…

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面板数据 Probit 模型的若干设定检验AI 解读

Generalized score and Wald tests are proposed to test certain aspects of the specification of panel probit models. The procedures used to detect misspecifications, such as omitted and superfluous variables, heteroscedasticity, nonnormality, and random coefficient variations, are designed specifically for the case when the model is estimated by sequential methods. The finite sample distributions of the test statistics in correctly and incorrectly specified models are…

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