A new alternative to the standard F test for clustered data

The data collection process and the inherent population structure are the main causes for clustered data. The observations in a given cluster are correlated, and the magnitude of such correlation is often measured by the intra-cluster correlation coefficient. The intra-cluster correlation can lead to an inflated size of the standard F test in a linear model. In this paper, we propose a solution to this problem. Unlike previous adjustments, our method does not require estimation of the intra-class correlation, which is problematic especially when the number of clusters is small. Our simulation results show that the new method outperforms the existing methods.     

Confidence interval estimation of the difference between paired AUCs based on combined biomarkers

In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice.     

Bayesian model comparison for compartmental models with applications in positron emission tomography

We develop strategies for Bayesian modelling as well as model comparison, averaging and selection for compartmental models with particular emphasis on those that occur in the analysis of positron emission tomography (PET) data. Both modelling and computational issues are considered. Biophysically inspired informative priors are developed for the problem at hand, and by comparison with default vague priors it is shown that the proposed modelling is not overly sensitive to prior specification. It is also shown that an additive normal error structure does not describe measured PET data well, despite being very widely used, and that within a simple Bayesian framework simultaneous parameter estimation and model comparison can be performed with a more general noise model. The proposed approach is compared with standard techniques using both simulated and real data. In addition to good, robust estimation performance, the proposed technique provides, automatically, a characterisation of the uncertainty in the resulting estimates which can be considerable in applications such as PET.     

Further results for parallel systems with two heterogeneous exponential components

In this paper, we investigate ordering properties of lifetimes of parallel systems with two independent heterogeneous exponential components with respect to likelihood ratio and hazard rate orders. Two sufficient conditions are provided for likelihood ratio and hazard rate orders to hold between the lifetimes of two parallel systems, respectively. Moreover, we extend the results from exponential case to the proportional hazard rate models. The results established here strength some of the results known in the literature. Finally, some numerical examples are given to illustrate the theoretical results derived here as well.     

Composite quantile regression for varying-coefficient single-index models

ABSTRACT

The varying-coefficient single-index model (VCSIM) is a very general and flexible tool for exploring the relationship between a response variable and a set of predictors. Popular special cases include single-index models and varying-coefficient models. In order to estimate the index-coefficient and the non parametric varying-coefficients in the VCSIM, we propose a two-stage composite quantile regression estimation procedure, which integrates the local linear smoothing method and the information of quantile regressions at a number of conditional quantiles of the response variable. We establish the asymptotic properties of the proposed estimators for the index-coefficient and varying-coefficients when the error is heterogeneous. When compared with the existing mean-regression-based estimation method, our simulation results indicate that our proposed method has comparable performance for normal error and is more robust for error with outliers or heavy tail. We illustrate our methodologies with a real example.     

On Redundancy Allocation to Series and Parallel Systems of Two Components

Abstract

For two components and one standby redundancy, we develop a characterization on the hazard rate order and the reversed hazard rate order of the redundant system lifetime in the context of mutually independent components lifetimes. Also, the likelihood ratio order is derived on the lifetime of the series system with two components lifetimes and two matched active redundancies lifetimes both following the proportional hazard model.     

An Inverse-Probability-Weighted Approach to the Estimation of Successive Duration Times under Left-Truncation and Right-Censoring

In incident cohort studies, survival data often include subjects who have had an initiate event at recruitment and may potentially experience two successive events (first and second) during the follow-up period. Since the second duration process becomes observable only if the first event has occurred, left-truncation and dependent censoring arise if the two duration times are correlated. To confront the two potential sampling biases, Chang and Tzeng (2006 Chang , S.-H. , Tzeng , S.-J. (2006). Noparametric estimation of sojourn time distributions for truncated serial event data- a weight-adjusted approach. Lifetime Data Anal. 53–67.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) provided an inverse-probability-weighted (IPW) approach for estimating the joint probability function of successive duration times. In this note, an alternative IPW approach is proposed. A simulation study is conducted to compare the two IPW approaches.     

青藏高原多民族聚居区民族交往的调查研究——以青海省化隆县为例

化隆地区多元民族类型和多种宗教信仰决定了当地民族关系的历史复杂性;当地的多民族杂居特点是我国青藏高原地区民族杂居形态的一个缩影,将化隆县作为一个多民族聚居区民族交往的调查研究个案,有助于我们比较准确地把握青藏地区民族交往的特点与规律.     

我国统计数据质量的评估方法研究————————趋势模拟评估法及其应用

 本文采用组合模型的形式对时间序列数据的变化特点建模，在模型通过各种检验、具有良好统计预测功能的基础上，从检验异常值的角度来分析预测值与实际值之间差异的程度，找出离群数据，利用数理统计中检验实验观测数据异常值的方法，对离群数据的误差进行统计上的显著检验，从而评估统计数据的质量。文章以我国国内生产总值（GDP）为研究对象，选取我国1978-2003年间的GDP作为样本，运用趋势模拟评估法来评估我国2004年国内生产总值的准确性。对我国经济指标的时间序列数据进行了实证分析。     

集体土地产权市场的地位和机制

土地资本的增殖动力始终是农村经济社会发展的原动力,国家土地制度应该反映城市和农村的共同土地利益要求.将国家土地制度理解为城镇国有土地以追求资产效益最大化为目的;农村集体土地以追求资源利益最大化为目的的分工,是一种不公正的社会价值观,只会扩大城乡差别,工农差别,加剧生态危机和粮食不安全因素.建立所有制平等的土地产权市场是发展的需要,利用土地资本市场的融资功能加大对农业产业化的投入是一种必然的选择.政府土地用途管制下的使用权市场应加以规范.