Suresh H. Moolgavkar  Ellen T. Chang  Georg Luebeck  Edmund C. Lau  Heather N. Watson  Kenny S. Crump  Paolo Boffetta  Roger McClellan 《Risk analysis》2015,35(4):663-675

To develop a quantitative exposure‐response relationship between concentrations and durations of inhaled diesel engine exhaust (DEE) and increases in lung cancer risks, we examined the role of temporal factors in modifying the estimated effects of exposure to DEE on lung cancer mortality and characterized risk by mine type in the Diesel Exhaust in Miners Study (DEMS) cohort, which followed 12,315 workers through December 1997. We analyzed the data using parametric functions based on concepts of multistage carcinogenesis to directly estimate the hazard functions associated with estimated exposure to a surrogate marker of DEE, respirable elemental carbon (REC). The REC‐associated risk of lung cancer mortality in DEMS is driven by increased risk in only one of four mine types (limestone), with statistically significant heterogeneity by mine type and no significant exposure‐response relationship after removal of the limestone mine workers. Temporal factors, such as duration of exposure, play an important role in determining the risk of lung cancer mortality following exposure to REC, and the relative risk declines after exposure to REC stops. There is evidence of effect modification of risk by attained age. The modifying impact of temporal factors and effect modification by age should be addressed in any quantitative risk assessment (QRA) of DEE. Until there is a better understanding of why the risk appears to be confined to a single mine type, data from DEMS cannot reliably be used for QRA.  相似文献   

    

Bradford W. Gutting  Andrey Rukhin  Ryan S. Mackie  David Marchette  Brandolyn Thran 《Risk analysis》2015,35(5):811-827

The application of the exponential model is extended by the inclusion of new nonhuman primate (NHP), rabbit, and guinea pig dose‐lethality data for inhalation anthrax. Because deposition is a critical step in the initiation of inhalation anthrax, inhaled doses may not provide the most accurate cross‐species comparison. For this reason, species‐specific deposition factors were derived to translate inhaled dose to deposited dose. Four NHP, three rabbit, and two guinea pig data sets were utilized. Results from species‐specific pooling analysis suggested all four NHP data sets could be pooled into a single NHP data set, which was also true for the rabbit and guinea pig data sets. The three species‐specific pooled data sets could not be combined into a single generic mammalian data set. For inhaled dose, NHPs were the most sensitive (relative lowest LD₅₀) species and rabbits the least. Improved inhaled LD₅₀s proposed for use in risk assessment are 50,600, 102,600, and 70,800 inhaled spores for NHP, rabbit, and guinea pig, respectively. Lung deposition factors were estimated for each species using published deposition data from Bacillus spore exposures, particle deposition studies, and computer modeling. Deposition was estimated at 22%, 9%, and 30% of the inhaled dose for NHP, rabbit, and guinea pig, respectively. When the inhaled dose was adjusted to reflect deposited dose, the rabbit animal model appears the most sensitive with the guinea pig the least sensitive species.  相似文献   

    

S. Hadi Khazraee  Antonio Jose Sáez‐Castillo  Srinivas Reddy Geedipally  Dominique Lord 《Risk analysis》2015,35(5):919-930

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.  相似文献   

    

Dimitrina S. Dimitrova  Vladimir K. Kaishev  Shouqi Zhao 《Risk analysis》2015,35(10):1919-1939

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time‐dependent critical risk level within a finite‐time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.  相似文献   

    

Kenny S. Crump  Cynthia Van Landingham  Suresh H. Moolgavkar  Roger McClellan 《Risk analysis》2015,35(4):676-700

The International Agency for Research on Cancer (IARC) in 2012 upgraded its hazard characterization of diesel engine exhaust (DEE) to “carcinogenic to humans.” The Diesel Exhaust in Miners Study (DEMS) cohort and nested case‐control studies of lung cancer mortality in eight U.S. nonmetal mines were influential in IARC's determination. We conducted a reanalysis of the DEMS case‐control data to evaluate its suitability for quantitative risk assessment (QRA). Our reanalysis used conditional logistic regression and adjusted for cigarette smoking in a manner similar to the original DEMS analysis. However, we included additional estimates of DEE exposure and adjustment for radon exposure. In addition to applying three DEE exposure estimates developed by DEMS, we applied six alternative estimates. Without adjusting for radon, our results were similar to those in the original DEMS analysis: all but one of the nine DEE exposure estimates showed evidence of an association between DEE exposure and lung cancer mortality, with trend slopes differing only by about a factor of two. When exposure to radon was adjusted, the evidence for a DEE effect was greatly diminished, but was still present in some analyses that utilized the three original DEMS DEE exposure estimates. A DEE effect was not observed when the six alternative DEE exposure estimates were utilized and radon was adjusted. No consistent evidence of a DEE effect was found among miners who worked only underground. This article highlights some issues that should be addressed in any use of the DEMS data in developing a QRA for DEE.  相似文献   

    

Andrew G. Huff  James S. Hodges  Shaun P. Kennedy  Amy Kircher 《Risk analysis》2015,35(8):1448-1467

To protect and secure food resources for the United States, it is crucial to have a method to compare food systems’ criticality. In 2007, the U.S. government funded development of the Food and Agriculture Sector Criticality Assessment Tool (FASCAT) to determine which food and agriculture systems were most critical to the nation. FASCAT was developed in a collaborative process involving government officials and food industry subject matter experts (SMEs). After development, data were collected using FASCAT to quantify threats, vulnerabilities, consequences, and the impacts on the United States from failure of evaluated food and agriculture systems. To examine FASCAT's utility, linear regression models were used to determine: (1) which groups of questions posed in FASCAT were better predictors of cumulative criticality scores; (2) whether the items included in FASCAT's criticality method or the smaller subset of FASCAT items included in DHS's risk analysis method predicted similar criticality scores. Akaike's information criterion was used to determine which regression models best described criticality, and a mixed linear model was used to shrink estimates of criticality for individual food and agriculture systems. The results indicated that: (1) some of the questions used in FASCAT strongly predicted food or agriculture system criticality; (2) the FASCAT criticality formula was a stronger predictor of criticality compared to the DHS risk formula; (3) the cumulative criticality formula predicted criticality more strongly than weighted criticality formula; and (4) the mixed linear regression model did not change the rank‐order of food and agriculture system criticality to a large degree.  相似文献   

    

ManMohan S. Sodhi 《Production and Operations Management》2015,24(9):1375-1389

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Nirpeksh Kumar  S. Lalitha 《统计学通讯:理论与方法》2013,42(5):820-828

The problem of multiple upper outlier detection in gamma sample is considered. Balasooriya and Gadag (1994 Balasooriya , U. , Gadag , V. ( 1994 ). Tests for upper outliers in the two-parameter exponential distribution . J. Statist. Computat. Simul. 50 : 249 – 259 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) proposed a location and scale invariant test based on the test statistic Z _k for testing the k upper outliers in two-parameter exponential sample. In this article, the test statistic is extended for gamma sample and the null distribution of the statistic is obtained. A simulation study is carried out to compare the performance of the tests and is found that the test based on Z _k is more powerful than the test based on the test statistic proposed by Jabbari Nooghabi et al. (2010 Jabbari Nooghabi , M. , Jabbari Nooghabi , H. , Nasiri , P. ( 2010 ). Detecting outliers in gamma distribution . Commun. Statist. Theor. Meth. 39 : 698 – 706 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).  相似文献   

    

Lichun Wang  Radhey S. Singh 《统计学通讯:理论与方法》2013,42(8):1315-1333

In the system of two seemingly unrelated regressions, employing a matrix power series, we show that the two-stage estimator is better than the ordinary least square estimator (OLSE) in terms of the mean square error matrix (MSEM) criterion. The result enriches the existing literature and can be applied to many fields of applications related to economics and statistics.  相似文献   

    

Tatsuya Kubokawa  Muni S. Srivastava 《统计学通讯:理论与方法》2013,42(15):2626-2642

The Akaike Information Criterion (AIC) is developed for selecting the variables of the nested error regression model where an unobservable random effect is present. Using the idea of decomposing the likelihood into two parts of “within” and “between” analysis of variance, we derive the AIC when the number of groups is large and the ratio of the variances of the random effects and the random errors is an unknown parameter. The proposed AIC is compared, using simulation, with Mallows' C _p , Akaike's AIC, and Sugiura's exact AIC. Based on the rates of selecting the true model, it is shown that the proposed AIC performs better.  相似文献