Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.     

试述图表资料在生物教学中的作用

图表资料具有直观性、系统性及概括性的特点,在生物教学中有着重要地位及作用．     

高校教材管理网络信息系统的设计与实现

介绍了一个适用于高校教材管理领域的网络信息系统,并对其总体结构及工作流程作了进一步探讨。     

Asymptotic Minimax Risk for the White Noise Model on the Sphere

Estimation of an unknown function on the unit sphere of the Euclidean space is considered. The function is observed in Gaussian continuous time white noise. Uniform norm is chosen as a loss function and exact asymptotic minimax risk is derived extending the result of Korostelev (1993). The exact asymptotic minimax risk is also given for the L ₂-loss, applying the result of Pinsker (1980).     

Robust modified profile estimating function with application to the generalized estimating equation

We consider methods for reducing the effect of fitting nuisance parameters on a general estimating function, when the estimating function depends on not only a vector of parameters of interest, θ$\theta$, but also on a vector of nuisance parameters, λ$\lambda$. We propose a class of modified profile estimating functions with plug-in bias reduced by two orders. A robust version of the adjustment term does not require any information about the probability mechanism beyond that required by the original estimating function. An important application of this method is bias correction for the generalized estimating equation in analyzing stratified longitudinal data, where the stratum-specific intercepts are considered as fixed nuisance parameters, the dependence of the expected outcome on the covariates is of interest, and the intracluster correlation structure is unknown. Furthermore, when the quasi-scores for θ$\theta$ and λ$\lambda$ are available, we propose an additional multiplicative adjustment term such that the modified profile estimating function is approximately information unbiased. This multiplicative adjustment term can serve as an optimal weight in the analysis of stratified studies. A brief simulation study shows that the proposed method considerably reduces the impact of the nuisance parameters.     

Foster care reunification: An exploration of non-linear hierarchical modeling

Hierarchical or multilevel models are based on the same fundamental concepts that apply to simple linear models. The linear forms of these models can be interpreted with relative ease as parameter estimates do not differ in magnitude or interpretation from standard non-hierarchical models. Non-linear hierarchical models, however, are more complex as the introduction of a random intercept means that parameter estimates must be interpreted as “subject-specific” rather than “population-averaged”. Depending on the specifics of the data being modeled, these parameters may be very different in magnitude. In this article we provide two examples of non-linear hierarchical modeling using administrative child welfare data. For each example, we estimate the odds of reunification for a cohort of children in California using both standard logistic regression models and random intercept models.     

视频点击流数据挖掘在远程教育中的应用

Web数据挖掘已经成为数据挖掘技术一个重要的应用领域,文章主要通过对远程教育网站的视频点击流日志文件进行数据挖掘,寻求用户访问规律,构建动态的个性化教育网站.     

Tests for homogeneity of risk differences in stratified design with correlated bilateral data

ABSTRACT

Correlated bilateral data arise from stratified studies involving paired body organs in a subject. When it is desirable to conduct inference on the scale of risk difference, one needs first to assess the assumption of homogeneity in risk differences across strata. For testing homogeneity of risk differences, we herein propose eight methods derived respectively from weighted-least-squares (WLS), the Mantel-Haenszel (MH) estimator, the WLS method in combination with inverse hyperbolic tangent transformation, and the test statistics based on their log-transformation, the modified Score test statistic and Likelihood ratio test statistic. Simulation results showed that four of the tests perform well in general, with the tests based on the WLS method and inverse hyperbolic tangent transformation always performing satisfactorily even under small sample size designs. The methods are illustrated with a dataset.     

瑶族石牌律研究的“三重证据法”

研究瑶族历史上的石牌文化,应采用文献资料、出土资料和口述资料三重证据的互证方法,才会有新发现、新收获和新突破,研究结论才会真实、可靠、科学,令人信服。     

Toward Best Practices in Analyzing Datasets with Missing Data: Comparisons and Recommendations

Although several methods have been developed to allow for the analysis of data in the presence of missing values, no clear guide exists to help family researchers in choosing among the many options and procedures available. We delineate these options and examine the sensitivity of the findings in a regression model estimated in three random samples from the National Survey of Families and Households (n = 250–2,000). These results, combined with findings from simulation studies, are used to guide answers to a set of 10 common questions asked by researchers when selecting a missing data approach. Modern missing data techniques were found to perform better than traditional ones, but differences between the types of modern approaches had minor effects on the estimates and substantive conclusions. Our findings suggest that the researcher has considerable flexibility in selecting among modern options for handling missing data.