Estimation of the Force of Infection from Current Status Data Using Generalized Linear Mixed Models

Based on sero-prevalence data of rubella, mumps in the UK and varicella in Belgium, we show how the force of infection, the age-specific rate at which susceptible individuals contract infection, can be estimated using generalized linear mixed models (McCulloch & Searle, 2001). Modelling the dependency of the force of infection on age by penalized splines, which involve fixed and random effects, allows us to use generalized linear mixed models techniques to estimate both the cumulative probability of being infected before a given age and the force of infection. Moreover, these models permit an automatic selection of the smoothing parameter. The smoothness of the estimated force of infection can be influenced by the number of knots and the degree of the penalized spline used. To determine these, a different number of knots and different degrees are used and the results are compared to establish this sensitivity. Simulations with a different number of knots and polynomial spline bases of different degrees suggest - for estimating the force of infection from serological data - the use of a quadratic penalized spline based on about 10 knots.     

进口对辽宁省经济增长贡献度的实证分析——基于时变参数卡尔曼滤波的估计

为了探寻辽宁对外经济发展的合理模式，从进口与经济增长间的关系入手，选用1985～2007年辽宁省的进口和地区生产总值数据，利用时变参数的分析方法对二者进行相关性分析，得出了进口对辽宁省的经济增长存在促进作用，而且这种作用随时递增的结论。因此，辽宁省应充分发挥进口对经济增长的积极作用，以快速实现辽宁老工业基地的振兴。     

医学图像分析技术及其应用的研究

信息图像化是一个受到广泛重视的研究课题,而图像的定量分析关系到图像中所包含的信息能否被很好的提取和利用.本文介绍了图像分析技术的原理及过程,着重介绍了自行研制的图像分析仪的应用实例.     

复杂岩性地区岩性识别与储层预测

中国陆相地层岩性成分较为复杂,岩性波阻抗值常呈多极分布。水动能强度的急剧变化、高频率的水进水退等沉积背景造成了薄互层广泛发育的特点。储层间干涉现象普遍存在,直接影响到地震岩性解释的精度。针对复杂岩性地区岩性–波阻抗关系复杂的特点,系统分析了造成传统地震储层预测方法解释误差的原因。根据复杂岩性的地球物理响应特点,选取对区分复杂岩性敏感的测井参数。同时,将90° 相位化地震数据作为测井参数反演的相对波阻抗约束数据体。研究结果表明,该方法对复杂岩性进行了有效的区分,达到了精细描述复杂岩性地区储层空间发育及平面展布特点的目的。     

深井水平井水平段水力延伸能力评价与分析

对影响水平井水平段延伸能力的因素进行了分析,然后根据钻井液流体力学理论,建立了水平井循环压耗计算模型,分别对水平井总循环压耗和水平段环空压耗进行计算,进而求出了水平井水平段极限延伸长度值;对钻井液密度、钻井泵额定压力、岩屑床高度和钻井液排量对水平段水力延伸能力的影响进行了分析。研究表明,水平段水力延伸能力受钻井液密度、钻井泵额定压力、岩屑床高度和钻井液排量等多个因素共同影响。为了提高深井水平井的延伸能力,应使用较低密度的钻井液;尽量保持较低的岩屑床高度;钻井液排量应尽量小。同时还认识到,深井水平井水力延伸能力主要受到钻井泵额定压力的制约。研发高额定压力的钻井泵,是提高深井水平井水力延伸能力的主要措施。     

On drift parameter estimation in models with fractional Brownian motion

We consider a stochastic differential equation involving standard and fractional Brownian motion with unknown drift parameter to be estimated. We investigate the standard maximum likelihood estimate of the drift parameter, two non-standard estimates and three estimates for the sequential estimation. Model strong consistency and some other properties are proved. The linear model and Ornstein–Uhlenbeck model are studied in detail. As an auxiliary result, an asymptotic behaviour of the fractional derivative of the fractional Brownian motion is established.     

Threshold‐free estimation of functional antibody titers of a group B streptococcus opsonophagocytic killing assay

Opsonophagocytic killing assays (OPKA) are routinely used for the quantification of bactericidal antibodies in blood serum samples. Quantification of the OPKA readout, the titer, provides the basis for the statistical analysis of vaccine clinical trials having functional immune response endpoints. Traditional OPKA titers are defined as the maximum serum dilution yielding a predefined bacterial killing threshold value, and they are estimated by fitting a dose‐response model to the dilution‐killing curve. This paper illustrates a novel definition of titer, the threshold‐free titer, which preserves biological interpretability while not depending on any killing threshold or on a postulated shape of the dose‐response curve. These titers are shown to be more precise than the traditional threshold‐based titers when using simulated and experimental group B streptococcus OPKA experimental data. Also, titer linearity is shown to be not measurable when using threshold‐based titers, whereas it becomes measurable using threshold‐free titers. The biological interpretability and operational characteristics demonstrated here indicate that threshold‐free titers are an appropriate tool for the routine analysis of OPKA data. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Asymptotic theory for maximum likelihood estimates in reduced-rank multivariate generalized linear models

Reduced-rank regression is a dimensionality reduction method with many applications. The asymptotic theory for reduced rank estimators of parameter matrices in multivariate linear models has been studied extensively. In contrast, few theoretical results are available for reduced-rank multivariate generalized linear models. We develop M-estimation theory for concave criterion functions that are maximized over parameter spaces that are neither convex nor closed. These results are used to derive the consistency and asymptotic distribution of maximum likelihood estimators in reduced-rank multivariate generalized linear models, when the response and predictor vectors have a joint distribution. We illustrate our results in a real data classification problem with binary covariates.     

Sample size re‐estimation incorporating prior information on a nuisance parameter

Prior information is often incorporated informally when planning a clinical trial. Here, we present an approach on how to incorporate prior information, such as data from historical clinical trials, into the nuisance parameter–based sample size re‐estimation in a design with an internal pilot study. We focus on trials with continuous endpoints in which the outcome variance is the nuisance parameter. For planning and analyzing the trial, frequentist methods are considered. Moreover, the external information on the variance is summarized by the Bayesian meta‐analytic‐predictive approach. To incorporate external information into the sample size re‐estimation, we propose to update the meta‐analytic‐predictive prior based on the results of the internal pilot study and to re‐estimate the sample size using an estimator from the posterior. By means of a simulation study, we compare the operating characteristics such as power and sample size distribution of the proposed procedure with the traditional sample size re‐estimation approach that uses the pooled variance estimator. The simulation study shows that, if no prior‐data conflict is present, incorporating external information into the sample size re‐estimation improves the operating characteristics compared to the traditional approach. In the case of a prior‐data conflict, that is, when the variance of the ongoing clinical trial is unequal to the prior location, the performance of the traditional sample size re‐estimation procedure is in general superior, even when the prior information is robustified. When considering to include prior information in sample size re‐estimation, the potential gains should be balanced against the risks.