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To study the homogeneity and influences on scientists'perspectives of environmental risks, we have examined similarities and differences in risk perceptions, particularly regarding nuclear wastes, and policy preferences among 1011 scientists and engineers. We found significant differences ( p 0.05)in the patterns of beliefs among scientists from different fields of research. In contrast to physicists, chemists, and engineers, life scientists tend to: (a)perceive the greatest risks from nuclear energy and nuclear waste management; (b)perceive higher levels of overall environmental risk; (c)strongly oppose imposing risks on unconsenting individuals; and (d)prefer stronger requirements for environmental management. On some issues related to priorities among public problems and calls for government action, there are significant variations among life scientists or physical scientists. We also found that–independently of field of research–perceptions of risk and its correlates are significantly associated with the type of institution in which the scientist is employed. Scientists in universities or state and local governments tend to see the risks of nuclear energy and wastes as greater than scientists who work as business consultants, for federal organizations, or for private research laboratories. Significant differences also are found in priority given to environmental risks, the perceived proximity of environmental disaster, willingness to impose risks on an unconsenting population, and the necessity of accepting risks and sacrifices.  相似文献   
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The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.  相似文献   
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On the run length of a Shewhart chart for correlated data   总被引:1,自引:0,他引:1  
We consider an extension of the classical Shewhart control chart to correlated data which was introduced by Vasilopoulos/Stamboulis (1978). Inequalities for the moments of the run length are given under weak conditions. It is proved analytically that the average run length (ARL) in the in-control state of the correlated process is larger than that in the case of independent variables. The exact ARL is calculated for exchangeable normal variables and autoregressive processes (AR). Moreover, we compare this chart with residual charts. Especially, in the case of an AR(1)—process with positive coefficient, it turns out that the out-of-control ARL of the modified Shewhart chart is smaller than that of the Shewhart chart for the residuals.  相似文献   
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We present a new characterization technique extracted from a well known idea in statistical inference. We use the partial derivative of the logarithm of the survival function in connection with truncated moments to characterize several probability distributions. Our methods introduce a unified technique to obtain several well known results in a unified way.  相似文献   
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What do voters really know about party platforms and how do they perceive the contents? Are there any relationships between party election platforms and electoral behavior? Despite of much research on parties, there are hardly any answers to these questions. If political parties devise programmes in order to influence political attitudes or electoral behavior, it will be necessary that these programmes are read by people. But it seems to be unclear if and how people do so. This article shows clearly that voters don’t know much about party manifestoes. Still, programmes are more important for voters than many people believe. Programmes are also an important factor for electoral behavior. But there is still a lack of data to get evident results.  相似文献   
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