A model of toxoplasmosis incidence in the UK: evidence synthesis and consistency of evidence

Summary.  We present a Bayesian evidence synthesis model combining data on seroprevalence, seroconversion and tests of recent infection, to produce estimates of current incidence of toxoplasmosis in the UK. The motivation for the study was the need for an estimate of current average incidence in the UK, with a realistic assessment of its uncertainty, to inform a decision model for a national screening programme to prevent congenital toxoplasmosis. The model has a hierarchical structure over geographic region, a random-walk model for temporal effects and a fixed age effect, with one or more types of data informing the regional estimates of incidence. Inference is obtained by using Markov chain Monte Carlo simulations. A key issue in the synthesis of evidence from multiple sources is model selection and the consistency of different types of evidence. Alternative models of incidence are compared by using the deviance information criterion, and we find that temporal effects are region specific. We assess the consistency of the various forms of evidence by using cross-validation where practical, and posterior and mixed prediction otherwise, and we discuss how these measures can be used to assess different aspects of consistency in a complex evidence structure. We discuss the contribution of the various forms of evidence to estimated current average incidence.     

An equivalence test for comparing DNA sequences

The practice of sequence alignment is constantly oscillating between the risk of overlooking important structure and that of discovering any arbitrarily defined kind of structure anywhere. On the other hand, the use of a condensed consensus sequence may lead to a substantial loss in valuable information. While adopting a Mahalanobis‐type index we allow for a certain degree of uncertainty in the measurements. This uncertainty may be caused by inaccurate measurements or ambiguity. In this paper, we test the similarity between DNA sequences within the framework of equivalence testing, accounting for both variances and covariances between frequencies of nucleotides. Statistical methods for testing equivalence were first developed in the context of pharmacokinetics and later extended to the field of clinical trials. Nowadays, (bio)equivalence tests seem to be less frequently used outside the drug testing field, including statistical genetics. Copyright © 2005 John Wiley & Sons, Ltd.     

Kin-related social organization in a winter population of the voleClethrionomys rufocanus

Kinship amongClethrionomys rufocanus was investigated during the winter of 1992/93 in a 3-ha enclosure using both molecular and catch-mark-release techniques. Forty-six adult voles (22 males and 24 females) having high heterozygosities, which were collected from several natural populations, were released into the enclosure on 29 September 1992. Most fall-born individuals of both sexes stayed in their natal site during the non-breeding period (December–March), although reproductively active females dispersed during the fall breeding season (October–November). These philopatric individuals aggregated and formed an maternal family in the winter. Several females which failed to reproduce were solitary during this season. Some individuals which were derived from several families also aggregated into a mixed lineage group. Survival rate of fall-born voles from earlier litters was higher than that from later ones. Maternal families broke up soon after the onset of spring reproduction. Most females established a territory near the wintering site and made a kincluster, in which close relatives neighbored each other. Maternal families in winter bring about female kin-clusters in spring, which may influence reproductive output in the breeding season.     

大学生心理健康教育的实践与探索

为了进一步加强大学生的心理健康教育,提高大学生的心理健康水平,论文结合我院心理健康教育的实践,从大学生心理健康教育的实际出发,简要分析了大学生心理健康教育的有效形式,探讨了大学生心理健康教育的有效途径:构建"多位一体"的大学生心理健康教育网;加强心理咨询工作;建立心理档案。     

Bounded Estimation in the Presence of Nuisance Parameters

The aim of this paper is to extend in a natural fashion the results on the treatment of nuisance parameters from the profile likelihood theory to the field of robust statistics. Similarly to what happens when there are no nuisance parameters, the attempt is to derive a bounded estimating function for a parameter of interest in the presence of nuisance parameters. The proposed method is based on a classical truncation argument of the theory of robustness applied to a generalized profile score function. By means of comparative studies, we show that this robust procedure for inference in the presence of a nuisance parameter can be used successfully in a parametric setting.     

SOME PROPERTIES OF PROFILE BOOTSTRAP CONFIDENCE INTERVALS

We consider the problem of finding an equi-tailed confidence interval, with coverage probability (1-α), for a scalar parameter θ₀ in the presence of a (possibly infinite dimensional) nuisance parameter ψ₀. It is supposed that the value taken by θ₀ does not restrict the value that ψ₀ may take and vice-versa. Given a sensible estimate ψ_n of ψ₀, profile bootstrap confidence interval for θ₀ is defined to be the exact equi-tailed confidence interval with coverage probability (1-α) assuming that ψ₀=ψ_n. We compare the properties of the profile bootstrap confidence interval and the ordinary bootstrap confidence interval when they are based on studentised and unstudentised quantities. Under mild regularity conditions the profile bootstrap confidence interval is always a subset of the set of allowable values of θ₀ and is transformation-respecting when based on either an unstudentised quantity or a studentised quantity satisfying certain restrictions. As a confidence interval for the autoregressive parameter of an AR(1) process, the profile bootstrap confidence interval has important advantages over the ordinary bootstrap confidence interval based on a studentised quantity.     

DNA双螺旋模型建立过程及其哲学思考

DNA双螺旋结构的发现,给人类社会带来巨大的影响．具有划时代的意义。回顾DNA双螺旋模型建立的背景和过程,科学家Wasron和Crick获得成功的因素不外乎：正确的科学方法、学科的交叉与融合、科学家完善的知识结构、良好的科研合作。青年科学工作者应当认真借鉴这些因素。     

中国边疆地区古代居民DNA研究

将现代分子生物学技术应用于考古学研究而形成的新兴的分支学科———分子考古学,利用分子研究技术,对出土的古代可研究对象进行分子水平的分析和研究。分子考古学对解决人类的起源、迁徙,动、植物的家养与驯化过程以及农业的起源和早期发展等重大考古问题,具有重要的意义。吉林大学边疆考古研究中心考古DNA实验室自1998年成立以来,先后对内蒙古、辽宁、吉林、河南、河北、新疆、青海等地多批古代人类遗骸进行了古DNA的提取和分析,初步建立了中国边疆地区古代居民的基因库,为研究中国边疆地区古代居民的人群构成、迁徙模式、混杂程度以及文化的传承与交流等问题,提供了宝贵的遗传学资料。     

A matching prior for the product of normal means based on the modified profile likelihood

In this paper, we develop a matching prior for the product of means in several normal distributions with unrestricted means and unknown variances. For this problem, properly assigning priors for the product of normal means has been issued because of the presence of nuisance parameters. Matching priors, which are priors matching the posterior probabilities of certain regions with their frequentist coverage probabilities, are commonly used but difficult to derive in this problem. We developed the first order probability matching priors for this problem; however, the developed matching priors are unproper. Thus, we apply an alternative method and derive a matching prior based on a modification of the profile likelihood. Simulation studies show that the derived matching prior performs better than the uniform prior and Jeffreys’ prior in meeting the target coverage probabilities, and meets well the target coverage probabilities even for the small sample sizes. In addition, to evaluate the validity of the proposed matching prior, Bayesian credible interval for the product of normal means using the matching prior is compared to Bayesian credible intervals using the uniform prior and Jeffrey’s prior, and the confidence interval using the method of Yfantis and Flatman.     

A semiparametric nonlinear mixed model approach to phase I profile monitoring

When process data follow a particular curve in quality control, profile monitoring is suitable and appropriate for assessing process stability. Previous research in profile monitoring focusing on nonlinear parametric (P) modeling, involving both fixed and random-effects, was made under the assumption of an accurate nonlinear model specification. Lately, nonparametric (NP) methods have been used in the profile monitoring context in the absence of an obvious linear P model. This study introduces a novel technique in profile monitoring for any nonlinear and auto-correlated data. Referred to as the nonlinear mixed robust profile monitoring (NMRPM) method, it proposes a semiparametric (SP) approach that combines nonlinear P and NP profile fits for scenarios in which a nonlinear P model is adequate over part of the data but inadequate of the rest. These three methods (P, NP, and NMRPM) account for the auto-correlation within profiles and treats the collection of profiles as a random sample with a common population. During Phase I analysis, a version of Hotelling’s T² statistic is proposed for each approach to identify abnormal profiles based on the estimated random effects and obtain the corresponding control limits. The performance of the NMRPM method is then evaluated using a real data set. Results reveal that the NMRPM method is robust to model misspecification and performs adequately against a correctly specified nonlinear P model. Control charts with the NMRPM method have excellent capability of detecting changes in Phase I data with control limits that are easily computable.