应用多水平统计模型评价职业性暴露的测量信度

探讨多水平统计模型在测量误差估计中的可应用性。方法:以云南锡业总公司劳动防护研究所提供的矿山井下作业环境中有害物质监测资料为例,分别进行2水平方盖成份模型和年份为固定效应的2水平混合效应模型拟合,根据模型参数和组间均分信度系数估计该资料的测量误差。结果:根据2个水平的随机效应参数,经计算得到氡、氡子体和粉尘的信度系数估计值,由测量信度均大于0.9可知资料的测量质量得到了较好的控制。结论:结果表明多水平统计模型适用于本资料的测量误差估计。当数据存在系统结构特征时,应采用能够正确反映数据结构、提供随机效应估计值的多水平统计模型,以获得较为准确的测量信度系数估计值。     

N-of-1无残留效应定量数据混合效应模型的模拟研究

目的 通过对不同时间点间存在相关、无残留效应的N-of-1定量数据进行模拟研究,比较不同检验方法的统计性能.方法 模拟参数设样本量为10(模型1),研究周期为3(模型2-4),不同时间点间相关系数为0.8(模型5-7),无残留效应,根据固定的效应差值产生多元正态分布数据,建立配对t检验、混合效应模型和差值的混合效应模型.使用效应差值估计值的Ⅰ类错误、检验功效、平均误差(ME),平均绝对误差(AE),均方误差(RMSE)评价各种模型.结果 所有模型估计值的均数都非常接近效应差值,所有模型估计值的ME、AE、RMSE都较小.除了模型7,其他模型的Ⅰ类错误概率都约等于0.05.随着效应差值的增大,所有模型的检验功效都随之增大.当两组的效应差值较小时(＜1.0),模型5的检验功效最大,模型2至模型4的功效较小.当两组的效应差值较大时(≥1.0),所有模型的功效都小于0.010.结论 混合效应模型比配对t检验更适合存在相关关系的N-of-1数据.混合效应模型的效果优于差值的混合效应模型,效果最优的模型是CS结构的混合效应模型.     

分类重复测量数据的非线性混合效应模型

[目的]探讨分类重复测量数据的非线性混合效应模型及SAS8.0软件NLMIXED过程实现。[方法]直接拟合分类反应变量的非线性概率模型,结合重复测量资料的特点,采用附加高斯积分来获得最大似然的参数估计。[结果]非线性混合效应模型能很好地拟合分类反应变量的重复测量资料,它允许固定效应和随机效应进入模型的非线性部分,可方便地分析随机缺失等非均衡数据。[结论]分类反应变量重复测量资料的非线性混合效应模型分析结果合理、容易解释,为分类重复测量资料提供一种新的分析思路。     

重复测量资料非线性混合效应模型应用与实现

目的探讨重复测量资料非线性分析技术、SAS软件NLMIXED过程及在群体药动学的应用.方法结合重复测量数据特点,采用最大似然原理进行参数估计,建立非线性混合效应参数模型.结果该模型不仅考虑了个体内和个体间变异,而且也考虑了参数间的非线性,允许固定效应和随机效应进入模型的非线性部分;可方便地分析随机缺失等非均衡数据;有助于引入其他解释变量时最佳模型的选择,更客观地解释其对代谢过程的影响.结论当重复测量资料不满足线性条件时,使用非线性混合效应模型能更客观地反映原数据特征,挖掘资料蕴藏的信息,弥补线性理论分析非线性重复测量资料之不足.     

混合线性模型的应用

目的介绍混合线性模型的结构，固定效应项和随机效应的含义。对具有内部相关性的资料．宣选用混合线性模型进行配合。方法用一个具有聚集性结构的例子和一个重复测量的例子说明配合混合线性模型的方法和步骤。结果分析了资料的层次结构，识别不同层次上的协变量，讨论了模型中固定效应矩阵和随机效应矩阵的结构，使模型参数估计值更易于理解和解释。由于混合线性模型克服了一般线性模型对反应变量必须具有独立和等方差的要求，从而扩大了线性模型的应用范围。对于具有聚集性质的资料及重复测量资料具有很好的拟合效果。结论这一模型计算较复杂，应用SAS／STAT软件包中的PROMIXED过程能很好地解决计算问题。     

医护人员职业紧张调查质量的信度评价

目的：对医护人员职业紧张的调查质量进行信度评价。方法：信度估计采用了同质性的cronbach-α系数以及固定与混合效应模型。结果：OSI-R量表的α系数和模型的信度估计结果与Osipow的结果一致，且优于国内同类研究。结论：本此调查结果可信，经过修订的OSI-R适合于对医护人员进行职业紧张评价。     

重复测量计数资料的随机效应ZINB模型

目的 阐明随机效应ZINB模型原理及其在零过多和过度离散并存时在重复测量计数资料中的应用.方法 将重复测量资料中的个体当作随机效应引进ZINB模型,建立随机效应ZINB模型.结果 模拟研究和实例分析表明,由于随机效应ZINB模型既考虑了个体在不同时点测量值间的相关性,又解决了零过多以及数据的过度离散问题,分析结果优于固定效应ZIP模型、随机效应ZIP模型以及固定效应ZINB模型.结论 对存在零过多,又具有过度离散的重复测量计数资料,更宜采用随机效应ZINB模型分析.     

交叉设计资料的混合效应模型分析

目的 放宽交叉设计方差分析对残留效应假定和探讨交叉设计混合效应分析模型。方法 建立三个模型以适应残留效应的不同假定，即残留效应为零、相等或不等，通过构造对数似然函数以及利用Fisher记分迭代算法可求得卢和口的极大似然估计与限制极大似然估计。结果 用SAS程序实现了交叉设计混合效应模型分析，得到了有关参数的估计值和直接处理效应的比较结果，实例分析表明，混合效应模型能够提供更多的有效信息。结论 混合效应模型较一般方差分析有更强的适应性，可完善和丰富交叉设计资料的分析方法。     

方差分析和混合线性模型在重复测量数据中的应用探讨

[目的]通过混合效应线性模型与重复测量的方差分析在重复测量资料中的应用比较,说明两种方法右处理重复测量资料时的特点.[方法]对四川大学华西医院精神科就诊的139名患者进行随访调查研究,对调查表中的抑郁量袭分数分别运用重复测量的方差分析模型和混合线性模型处理.[结果]混合效应模型和重复测量的方差分析都是处理重复测量资科的重要的统计方法,前者在选择协方差结构下可对重复测量资料的固定效应和随机效应参数及协方差矩阵进行参数估计和统计检验,后者只能对重复测量资料的固定效应做出统计推断.[结论]混合效应模型在处理临床中的重复测量的资料比重复测量的方差分析,对资料的要求更宽松,所得的结果更加客观.     

重复测量计数资料的随机效应ZIP模型

目的 探索重复测量0过多计数资料的统计模型.方法 将重复测量中的个体当作随机效应引进ZIP模型,建立随机效应ZIP模型.结果 模拟研究和实例分析表明,由于随机效应ZIP模型既考虑了个体不同测量值的相关性,又考虑了0过多的问题,结果优于随机效应Poisson回归和固定效应ZIP模型.结论 在重复测量计数资料0过多时,宜采用随机效应ZIP模型.     

Two dimensions of measurement error: classical and Berkson error in residential radon exposure assessment

Measurement error in exposure assessment is unavoidable. Statistical methods to correct for such errors rely upon a valid error model, particularly regarding the classification of classical and Berkson error, the structure and the size of the error. We provide a detailed list of sources of error in residential radon exposure assessment, stressing the importance of (a) the differentiation between classical and Berkson error and (b) the clear definitions of predictors and operationally defined predictors using the example of two German case-control studies on lung cancer and residential radon exposure. We give intuitive measures of error size and present evidence on both the error size and the multiplicative structure of the error from three data sets with repeated measurements of radon concentration. We conclude that modern exposure assessment should not only aim to be as accurate and precise as possible, but should also provide a model of the remaining measurement errors with clear differentiation of classical and Berkson components.     

Residential radon exposure and lung cancer: variation in risk estimates using alternative exposure scenarios

The most direct way to derive risk estimates for residential radon progeny exposure is through epidemiologic studies that examine the association between residential radon exposure and lung cancer. However, the National Research Council concluded that the inconsistency among prior residential radon case-control studies was largely a consequence of errors in radon dosimetry. This paper examines the impact of applying various epidemiologic dosimetry models for radon exposure assessment using a common data set from the Iowa Radon Lung Cancer Study (IRLCS). The IRLCS uniquely combined enhanced dosimetric techniques, individual mobility assessment, and expert histologic review to examine the relationship between cumulative radon exposure, smoking, and lung cancer. The a priori defined IRLCS radon-exposure model produced higher odds ratios than those methodologies that did not link the subject's retrospective mobility with multiple, spatially diverse radon concentrations. In addition, the smallest measurement errors were noted for the IRLCS exposure model. Risk estimates based solely on basement radon measurements generally exhibited the lowest risk estimates and the greatest measurement error. The findings indicate that the power of an epidemiologic study to detect an excess risk from residential radon exposure is enhanced by linking spatially disparate radon concentrations with the subject's retrospective mobility.     

Modeling joint exposures and health outcomes for cumulative risk assessment: the case of radon and smoking

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors.     

Theoretical study of the relation between radon and its long-lived progeny in a room

We present a theoretical study of the complex relation between radon and its long-lived progeny implanted in glass surfaces. The well known (extended) Jacobi room model, which is normally used to describe radon and its progeny in a room, was transformed into a two-parameter model revealing a linear correlation between long term radon exposure and surface activity due to implanted radon decay products. Furthermore, this new approach made integration into a Monte Carlo simulation possible so that the large variation of different room model parameters could be taken into account. This allowed the calculation of a probability distribution for radon exposure from the measurement of the implanted 210Po activity. The availability of a 95% confidence interval for the radon exposure is valuable in the application of retrospective radon assessment in epidemiological studies.     

Contamination of individuals by radon daughters: a preliminary study

Body radon daughter contamination reflects relative individual respiratory exposures to radon daughters; counts can be related both to household radon levels and to lung cancer risk factors such as sex and tobacco smoking. Radon daughters were counted by gamma spectroscopy from 180 adult residents of eastern Pennsylvania. A seven-position, 35-min scan was conducted in a mobile body counter, generally during afternoon or evening hours. Track-etch detectors for household radon were distributed, and were recovered from 80% of the subjects. Over 75% of the population had environmentally enhanced radon daughter contamination. House radon levels were strongly related, as anticipated, to radon daughter contamination in the 112 subjects for whom both sets of measurements were available (p less than .001); basement measurements were as strongly related to personal contamination as were living area measurements; bedroom measurements were slightly more strongly correlated. Both sex (p less than .02) and cigarette smoking (p less than .01) significantly modified the relationships, after nonlinear adjustment for travel times. Using a logarithmic model, a given house living-area radon level was associated in females with body contamination by radon daughters 2-3 times that in males. Nonsmokers had 2-4 times higher levels of contamination than smokers. Results are for the total of internal and external contamination, these being highly correlated in preliminary experiments. Time usage and activity patterns of the subjects are believed to be important in explaining these findings, and may become important variables in radon risk assessment.     

Spatial and temporal indoor radon variations.

This paper examines the ability of standard radon measurement protocols to predict long-term radon concentrations in houses located in the upper Midwest. It was observed that: (1) significant radon variations can occur on a spatial scale as small as a single floor; (2) radon measurements that integrate for periods less than 3 mo are reliable only to within a factor of 2 or more; and (3) contemporary, short-term measurements within existing structures may not accurately reflect past radon concentrations. Two-hundred forty-three occupied houses located in 40 towns were monitored for at least 1 y using alpha-track detectors. If lifetime radon exposure estimates need to be determined accurately, then long-term, integrating radon detectors should be placed in several rooms of each house. In radon atmospheres that may not be stable for long periods of time, it is suggested that multiple, year-long measurements or surface alpha activity measurements in combination with year-long alpha-track measurements are needed for an accurate lifetime radon assessment.     

Iowa radon leukaemia study: a hierarchical population risk model for spatially correlated exposure measured with error

This paper presents a Bayesian model that allows for the joint prediction of county-average radon levels and estimation of the associated leukaemia risk. The methods are motivated by radon data from an epidemiologic study of residential radon in Iowa that include 2726 outdoor and indoor measurements. Prediction of county-average radon is based on a geostatistical model for the radon data which assumes an underlying continuous spatial process. In the radon model, we account for uncertainties due to incomplete spatial coverage, spatial variability, characteristic differences between homes, and detector measurement error. The predicted radon averages are, in turn, included as a covariate in Poisson models for incident cases of acute lymphocytic (ALL), acute myelogenous (AML), chronic lymphocytic (CLL), and chronic myelogenous (CML) leukaemias reported to the Iowa cancer registry from 1973 to 2002. Since radon and leukaemia risk are modelled simultaneously in our approach, the resulting risk estimates accurately reflect uncertainties in the predicted radon exposure covariate. Posterior mean (95 per cent Bayesian credible interval) estimates of the relative risk associated with a 1 pCi/L increase in radon for ALL, AML, CLL, and CML are 0.91 (0.78-1.03), 1.01 (0.92-1.12), 1.06 (0.96-1.16), and 1.12 (0.98-1.27), respectively.     

哈尔滨工程大学室内氡浓度水平及评价

目的 了解哈尔滨工程大学室内氡浓度的水平,并进行剂量水平评价。方法 采用双滤膜法连续测量哈尔滨工程大学室内氡浓度,并对氡的危害进行评价。结果 哈尔滨工程大学室内氡及其子体对人体造成的年辐射剂量为1.48 mSv,略高于我国平均水平。结论 哈尔滨工程大学室内氡浓度偏高,可以从"截源"、"消散"两个方面来降低室内氡浓度。     

Determination of the radon diffusion length in building materials using electrets and activated carbon

This work presents a technique for determining the radon (222Rn) diffusion length in porous materials. A mathematical model that describes the process of radon diffusion in a closed chamber, divided into two sections by a porous building material, is proposed. The derived relations allow evaluating the radon diffusion length in the material from measurements of the radon concentrations in the two sections. Preliminary experimental results are presented for the diffusion lengths of concrete and gypsum obtained by measuring the radon concentration via two standard passive detection methods: electrostatic electret chambers and activated charcoal canisters. The electret measurements were checked by a solid state continuous radon monitor.     

Glass-based radon-exposure assessment and lung cancer risk

Lung cancer risk estimation in relation to residential radon exposure remains uncertain, partly as a result of imprecision in air-based retrospective radon-exposure assessment in epidemiological studies. A recently developed methodology provides estimates for past radon concentrations and involves measurement of the surface activity of a glass object that has been in a subject's dwellings through the period for exposure assessment. Such glass measurements were performed for 110 lung cancer subjects, diagnosed 1985 to 1995, and for 231 control subjects, recruited in a case-control study of residential radon and lung cancer among never-smokers in Sweden. The relative risks (with 95% confidence intervals) of lung cancer in relation to categories of surface-based average domestic radon concentration during three decades, delimited by cutpoints at 50, 80, and 140 Bq m(-3), were 1.60 (0.8 to 3.4), 1.96 (0.9 to 4.2), and 2.20 (0.9 to 5.6), respectively, with average radon concentrations below 50 Bq m(-3) used as reference category, and with adjustment for other risk factors. These relative risks, and the excess relative risk (ERR) of 75% (-4% to 430%) per 100 Bq m(-3) obtained when using a continuous variable for surface-based average radon concentration estimates, were about twice the size of the corresponding relative risks obtained among these subjects when using air-based average radon concentration estimates. This suggests that surface-based estimates may provide a more relevant exposure proxy than air-based estimates for relating past radon exposure to lung cancer risk.