响应变量为多维时因果推断中混杂因子的控制和排序

研究可交换条件下多维结构回归模型中总体平均处理效应的混杂因子的控制和排序问题,利用矩阵的迹定义混杂因子的控制效率,通过控制效率来控制混杂因子,并给出混杂因子的排序,同时给出一个应用实例。     

谈卫生事业单位电算化会计系统中的内部控制

伴随着科技的发展，电算化会计在各企事业单位中的普及，对内部控制制度的冲击产生了一些新问题，通过分析内部控制现状厦电算化对内部控制的影响，阐述了使其适应发展趋势的几点建议。     

复杂疾病关联研究中的若干问题

关联研究广泛应用于阐述心血管疾病、2型糖尿病、原发性高血压和肥胖等人类复杂疾病的遗传学基础。文中就关联研究中混杂的识别与控制、候选基因的选择、中间表型的应用、单体型分析方法的应用,以及结果的判定等问题进行了讨论。人群分层是关联研究混杂的主要来源之一。选择患者亲属做对照、基因组对照和选择遗传背景较为一致的隔离人群都可以减少混杂。候选基因的选择可以基于与疾病间的生物学联系或是该基因与疾病某已知相关基因的同源性。适当的应用中间表型和单体型分析方法可以增加关联研究有意义发现的机会。本文认为,优化研究设计、足够的样本含量、正确选择对照,结合先进的数据分析方法,关联研究必将为困扰人类的常见疾病的易感性研究发挥更大的作用。     

眼－头运动协同中头部运动的双重模式控制

本文通过目标运动引起的眼－头运动协同的实验，测量和分析了头部运动的动态特性来探讨其头部运动的控制机制。研究结果揭示了眼－头协同的注视运动中头部运动的双重模式控制机制：在小幅度运动范围是线性比例控制，在大幅度运动范围是使用最大作用力的Ｂａｎｇ－Ｂａｎｇ开关控制。     

加强医疗欠费的内部控制探讨

“债权和债务”内部控制点中的医疗欠费对医院的风险影响越来越大。根据医疗欠费形成的过程，对医疗欠费内部控制流程进行分析，通过明确控制要点和控制方法，找出薄弱环节，进而提出完善医疗欠费内部控制的几点建议。     

基于微生物洁净室管理与检测质量控制规程的探讨

洁净室在微生物检测过程中发挥着重要作用，会极大地影响微生物检测结果的准确性。洁净室的洁净度是影响洁净室发挥作用的关键因素，因此应该加强微生物洁净室管理，同时构建更加完善的检测质量控制规程，切实保障微生物洁净室的管理效果，提升洁净室的洁净度。基于此，文章从微生物检测入手分析了微生物洁净室管理方法，并对微生物检测质量控制规程进行了探究。     

一类时滞单神经元模型的Hopf分岔混杂控制（英文）

本文考虑了一类时滞单神经元模型的Hopf分岔混杂控制.选择时滞为分岔参数,可以证明,当时滞经过一个临界值时,发生了Hopf分岔.然而,通过调整混合控制策略的控制参数,在不需要这种分岔的情况下,Hopf分岔被延迟.数值模拟结果表明,控制策略在控制Hopf分岔方面是有效的.     

美国西北部森林动物危害控制研究动态

美国西北部森林动物危害控制研究动态张知彬（中国科学院动物研究所北京１０００８０）关键词动物危害控制，森林生态系统，免疫不育，美国１危害状况华盛顿州和俄勒冈州是美国西部的重要森林基地。松树（Ｐｉｎｕｓｐｏｎｄｅｒｏｓａ）、雪杉（Ｐｓｅｕｄｏｔｓｕｇａｔ...     

基于京医通系统的医院货币资金内部控制建设

京医通业务系统启动后，推行了线上挂号缴费业务，在一定程度上提高医院工作效率，提升患者就医体验，改善患者就医环境。但同时也带来了一些内部控制特别是资金安全管理的风险，针对这些风险，采取了相应的控制措施，加强内部控制管理和风险防范。     

国内外哮喘控制评价量表的研究进展与应用

"哮喘控制"是指可在患者中观察到的,通过治疗减少或消除的哮喘症状程度。支气管哮喘全球倡议指南(GINA)通过肺功能、气道高反应性和控制评价量表等工具来评价患者哮喘控制程度。其中,哮喘控制评价量表在疾病评估中占有重要地位。本文基于哮喘控制概念发展的四个阶段,梳理不同阶段国内外哮喘控制评价量表,总结量表临床应用研究的主要结论,对未来制定更全面、更符合临床的哮喘控制量表提出建议。     

Confounding in epidemiologic studies: the adequacy of the control group as a measure of confounding

A model for confounding in epidemiologic studies is developed based on the adequacy of the "control" group, instead of the widely used criterion of collapsibility, as a measure of confounding. It is shown that conditions for no confounding in both cohort and case-control studies derived under this model generally agree with the conditions for confounding derived inductively by Miettinen and Cook (1981, American Journal of Epidemiology 114, 593-603). The concept of confounding on which this model is based is compared with the collapsibility criterion in terms of its utility in the design and analysis of epidemiologic studies.     

Age correction in dementia--matching to a healthy brain

In recent research, many univariate and multivariate approaches have been proposed to improve automatic classification of various dementia syndromes using imaging data. Some of these methods do not provide the possibility to integrate possible confounding variables like age into the statistical evaluation. A similar problem sometimes exists in clinical studies, as it is not always possible to match different clinical groups to each other in all confounding variables, like for example, early-onset (age<65 years) and late-onset (age≥65) patients with Alzheimer's disease (AD). Here, we propose a simple method to control for possible effects of confounding variables such as age prior to statistical evaluation of magnetic resonance imaging (MRI) data using support vector machine classification (SVM) or voxel-based morphometry (VBM). We compare SVM results for the classification of 80 AD patients and 79 healthy control subjects based on MRI data with and without prior age correction. Additionally, we compare VBM results for the comparison of three different groups of AD patients differing in age with the same group of control subjects obtained without including age as covariate, with age as covariate or with prior age correction using the proposed method. SVM classification using the proposed method resulted in higher between-group classification accuracy compared to uncorrected data. Further, applying the proposed age correction substantially improved univariate detection of disease-related grey matter atrophy using VBM in AD patients differing in age from control subjects. The results suggest that the approach proposed in this work is generally suited to control for confounding variables such as age in SVM or VBM analyses. Accordingly, the approach might improve and extend the application of these methods in clinical neurosciences.     

A comparison of approaches to control for confounding factors by regression models

A common technique to control for confounding factors in practice is by regression adjustment. There are various versions of regression modeling in the literature, and in this paper we considered four approaches often seen in genetic association studies. We carried out both analytical and simulation studies comparing the bias of effect size estimates and examining the test sizes under the null hypothesis of no association between an outcome and an exposure. Further, we compared the methods in a nonsynonymous genome-wide scan for plasma lipoprotein(a) levels using a dataset from the Dallas Heart Study. We found that a widely employed approach that models the covariate-adjusted outcome and the exposure leads to an infranominal test size and underestimation of the exposure effect size. In conclusion, we recommend either using multiple regression models or modeling the covariate-adjusted outcome and the covariate-adjusted exposure to control for confounding factors.     

A field study on the influence of food and immune priming on a bumblebee–gut parasite system

Laboratory experiments are often preferred over field experiments because they allow the control of confounding factors that would otherwise influence the causal effect of a particular focal experimental factor. These confounding factors can, however, significantly alter the response of an organism confronted with a particular situation, which can have great implications. In a field experiment with a bumblebee host–parasite system, we looked at the influence of additional food supply and immune challenge on various colony fitness values and parasite traits. We could confirm the importance of food on the colony fitness, but not on parasite infection probability or parasite genetic diversity. In contrast to the findings of laboratory experiments of this system, challenge of the immune system had no significant effect on colony fitness or parasite infections. These results likely reflect an overriding effect of environmental variation without disproving the concept of a cost of defence per se. But the results also demonstrate that confounding factors purposely controlled for in the laboratory have to be weighed against their ecological relevance, and stress the need for careful analysis before any direct transfer is made of laboratory results to field situations.     

Control of confounding of genetic associations in stratified populations

To control for hidden population stratification in genetic-association studies, statistical methods that use marker genotype data to infer population structure have been proposed as a possible alternative to family-based designs. In principle, it is possible to infer population structure from associations between marker loci and from associations of markers with the trait, even when no information about the demographic background of the population is available. In a model in which the total population is formed by admixture between two or more subpopulations, confounding can be estimated and controlled. Current implementations of this approach have limitations, the most serious of which is that they do not allow for uncertainty in estimations of individual admixture proportions or for lack of identifiability of subpopulations in the model. We describe methods that overcome these limitations by a combination of Bayesian and classical approaches, and we demonstrate the methods by using data from three admixed populations--African American, African Caribbean, and Hispanic American--in which there is extreme confounding of trait-genotype associations because the trait under study (skin pigmentation) varies with admixture proportions. In these data sets, as many as one-third of marker loci show crude associations with the trait. Control for confounding by population stratification eliminates these associations, except at loci that are linked to candidate genes for the trait. With only 32 markers informative for ancestry, the efficiency of the analysis is 70%. These methods can deal with both confounding and selection bias in genetic-association studies, making family-based designs unnecessary.     

The sign of the bias of unmeasured confounding

Summary .   Unmeasured confounding variables are a common problem in drawing causal inferences in observational studies. A theorem is given which in certain circumstances allows the researcher to draw conclusions about the sign of the bias of unmeasured confounding. Specifically, it is possible to determine the sign of the bias when monotonicity relationships hold between the unmeasured confounding variable and the treatment, and between the unmeasured confounding variable and the outcome. Some discussion is given to the conditions under which the theorem applies and the strengths and limitations of using the theorem to assess the sign of the bias of unmeasured confounding.     

Measurement of Apolipoprotein E (apoE) in Cerebrospinal Fluid

Apolipoprotein E (apoE) is a protein involved in transport of lipids and has been implicated to play an important role in regeneration after nerve injury. Determination of apoE in cerebrospinal fluid (CSF) thus have a potential interest when studying different forms of brain damage and as a marker of ongoing regenerative processes in the brain. However, previous studies on CSF-ApoE in Alzheimer's disease (AD) have given inconclusive results. Such inconsistant results might be related to confounding factors interfering with sample handling and/or analyses, which have not been fully elucidated. We therefore examined different potential confounding factors for analyses of apoE in CSF and also developed a new enzyme linked immunosorbent assay (ELISA). The hydrophobic character of ApoE resulted in adsorbtion to different types of test tubes commonly used for collection of CSF at lumbar puncture, resulting in falsly low levels. This makes CSF handling critical, especially if samples are taken in different types of tubes, or is transferred to new tubes. Taking this confounding factors in consideration and analysing patient and control CSF handled in the same way and using the new ELISA, we could confirm our previous finding of reduced levels of ApoE in AD, (3.4 ± 1.3mg/l) compared with controls (4.5 ± 2.7mg/l) (p = 0.045). Both in the AD and in the control group, higher levels of CSF-ApoE was found in individuals possessing the ApoE4 alleles. Our results support that CSF-ApoE is reduced in AD, and that handling of CSF is a critical factor, which may explain the discrepant results from previous studies. Differences in the amount of patients and controls possessing the ApoE4 allele included might also increase the variance between different studies.     

An experimental investigation into the effects of traffic noise on distributions of birds: avoiding the phantom road

Many authors have suggested that the negative effects of roads on animals are largely owing to traffic noise. Although suggestive, most past studies of the effects of road noise on wildlife were conducted in the presence of the other confounding effects of roads, such as visual disturbance, collisions and chemical pollution among others. We present, to our knowledge, the first study to experimentally apply traffic noise to a roadless area at a landscape scale—thus avoiding the other confounding aspects of roads present in past studies. We replicated the sound of a roadway at intervals—alternating 4 days of noise on with 4 days off—during the autumn migratory period using a 0.5 km array of speakers within an established stopover site in southern Idaho. We conducted daily bird surveys along our ‘Phantom Road’ and in a nearby control site. We document over a one-quarter decline in bird abundance and almost complete avoidance by some species between noise-on and noise-off periods along the phantom road and no such effects at control sites—suggesting that traffic noise is a major driver of effects of roads on populations of animals.