Duration analysis in longitudinal studies with intermittent observation times and losses to followup

We consider the analysis of spell durations observed in event history studies where members of the study panel are seen intermittently. Challenges for analysis arise because losses to followup are frequently related to previous event history, and spells typically overlap more than one observation period. We provide methods of estimation based on inverse probability of censoring weighting for parametric and semiparametric Cox regression models. Selection of panel members through a complex survey design is also addressed, and the methods are illustrated in an analysis of jobless spell durations based on data from the Statistics Canada Survey of Labour and Income Dynamics. The Canadian Journal of Statistics 40: 1–21; 2012 © 2012 Statistical Society of Canada     

A Note on Goodness-of-Fit Test in Latent Variable Models with Categorical Variables

Assessing the goodness-of-fit of latent variable models for categorical data becomes a problem in presence of sparse data since the classical goodness-of-fit statistics are badly approximated by the chi square distribution. A good solution to this problem is represented by statistical tests based on the residuals associated to marginal distributions of the manifest variables (Cagnone and Mignani, 2007 Cagnone , S. , Mignani , S. ( 2007 ). Assessing the goodness-of-fit of a latent variable model for ordinal data . Metron LXV : 337 – 361 . [Google Scholar]; Maydeu-Olivares and Joe, 2005 Maydeu-Olivares , A. , Joe , H. ( 2005 ). Limited- and full-information estimation and goodness-of-fit testing in 2n contingency tables: A unified framework . J. Amer. Statist. Assoc. 100 ( 471 ): 1009 – 1020 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]; Reiser, 1996 Reiser , M. ( 1996 ). Analysis of residual for the multinomial item response model . Psychometrika 61 : 509 – 528 .[Crossref], [Web of Science ®] , [Google Scholar]). The quadratic form associated to the test involves the use of a generalized inverse of the covariance matrix of the sample proportions. In this article we prove that the rank of the Moore-Penrose generalized inverse is univocally determined and hence it can be used appropriately.     

The weighted least square based estimators with censoring indicators missing at random

In this paper, we study linear regression analysis when some of the censoring indicators are missing at random. We define regression calibration estimate, imputation estimate and inverse probability weighted estimate for the regression coefficient vector based on the weighted least squared approach due to Stute (1993), and prove all the estimators are asymptotically normal. A simulation study was conducted to evaluate the finite properties of the proposed estimators, and a real data example is provided to illustrate our methods.     

逆半直积上的自然序关系

利用逆半直积的性质刻划了逆半直积的自然序关系,讨论了逆半直积的闭包.     

对角优势化的实現

对角优势化是INA法的关键。本文对对角优势化问題进行了直接研究。给出了可实现条件和关于计算特征值的降阶方程的定理。最后,讨论了一种简便而有效的局部补偿方法。     

分解、拟合和对角优势

本文提出一种有有事分式阵作为预补偿阵以实现对角优势的新方法,先将对象传递阵和预补偿阵进行适当的分解,使待解方程的结构变得简单,再分别用极小化方法和最小二乘法术预补偿阵。通过实例计算证明本文所迷方法是成功的。     

英语短语动词的三要素——以away组成的含gradually之义的短语动词为例

从语义的角度来对短语动词进行系统地认知是一种科学的新理念、新方法.以短语动词中的副词或介词为主线来进行纵向的组群亦是切实可行的一种好方法.然后在横向上辨析相关的同义的短语.以三者的有机结合所形成的复合思维来加以认知则更具特色.由away组成的短语动词可表数个意义.含"gradually"之义时,所表意义为动状关系.     

Inference from Accelerated Degradation and Failure Data Based on Gaussian Process Models

An important problem in reliability and survival analysis is that of modeling degradation together with any observed failures in a life test. Here, based on a continuous cumulative damage approach with a Gaussian process describing degradation, a general accelerated test model is presented in which failure times and degradation measures can be combined for inference about system lifetime. Some specific models when the drift of the Gaussian process depends on the acceleration variable are discussed in detail. Illustrative examples using simulated data as well as degradation data observed in carbon-film resistors are presented.     

Bayesian approach to the inverse problem in a light scattering application

In this article, static light scattering (SLS) measurements are processed to estimate the particle size distribution of particle systems incorporating prior information obtained from an alternative experimental technique: scanning electron microscopy (SEM). For this purpose we propose two Bayesian schemes (one parametric and another non-parametric) to solve the stated light scattering problem and take advantage of the obtained results to summarize some features of the Bayesian approach within the context of inverse problems. The features presented in this article include the improvement of the results when some useful prior information from an alternative experiment is considered instead of a non-informative prior as it occurs in a deterministic maximum likelihood estimation. This improvement will be shown in terms of accuracy and precision in the corresponding results and also in terms of minimizing the effect of multiple minima by including significant information in the optimization. Both Bayesian schemes are implemented using Markov Chain Monte Carlo methods. They have been developed on the basis of the Metropolis–Hastings (MH) algorithm using Matlab^® and are tested with the analysis of simulated and experimental examples of concentrated and semi-concentrated particles. In the simulated examples, SLS measurements were generated using a rigorous model, while the inversion stage was solved using an approximate model in both schemes and also using the rigorous model in the parametric scheme. Priors from SEM micrographs were also simulated and experimented, where the simulated ones were obtained using a Monte Carlo routine. In addition to the presentation of these features of the Bayesian approach, some other topics will be discussed, such as regularization and some implementation issues of the proposed schemes, among which we remark the selection of the parameters used in the MH algorithm.     

运用Leontief逆矩阵进行完全关联分析暗含假设条件

完全关联分析通常以Leontief逆矩阵为基础,而Leontief逆矩阵的计算又以竞争型投入产出表为数据来源。经推导发现：以竞争型投入产出表为数据来源计算Leontief逆矩阵暗含假设条件,国内产业的直接消耗系数矩阵等于国外产业的直接消耗系数矩阵。根据OECD提供的投入产出数据验证该假设条件,其结论是该假设条件不能满足,故在完全关联分析中要以非竞争型投入产出表为数据来源,因为非竞争型投入产出表区分了国产品与进口品的中间使用和最终使用,而且以非竞争型投入产出表为数据来源进行完全关联分析不受上述假设条件的限制。