Thomas E. McKone  Lydia Feng 《Risk analysis》2015,35(11):2087-2101

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.  相似文献   

    

Anne E. Smith 《Risk analysis》2015,35(3):381-384

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Ivan E. Brick  Oded Palmon  Itzhak Venezia 《European Management Review》2015,12(2):99-111

Bowman's (1980, 1982, 1984) finding of a negative relationship between the means and variances of accounting returns (the Bowman Paradox) spurred a considerable literature analyzing this phenomenon. The sign of the relationship between the mean return on equity (ROE) and its standard deviation remains unresolved. Concerns were raised about ROE measurement and statistical techniques used in establishing the paradox. The papers critiquing (and supporting) it were mostly limited in scope, studied only short periods of time and provided limited robustness checks. In addition, no paper considered the effect of issuances and repurchase of stocks on the measurement of ROE. This study revisits the Paradox and addresses the above mentioned deficiencies in prior research. We use data from longer periods, control for size and leverage and provide additional robustness checks. We conclude that a positive relationship between mean ROE and its standard deviation is far more likely than a negative one.  相似文献   

    

David E. Cantor  Paula C. Morrow  Jennifer Blackhurst 《决策科学》2015,46(4):697-729

Employee engagement in environmental behaviors is an important topic in operations management. Drawing upon stakeholder, commitment, and organizational support theories, this study creates and tests an empirical model of how store managers (i.e., supervisors) influence their direct reports (i.e., subordinates) to become engaged in environmental behaviors. Based on a dataset derived from supervisors and their subordinates who are employed at the same grocery store location across a large retail grocery chain, we test our study's nomological model and find support for the linkages proposed. Key research and managerial implications are discussed.  相似文献   

    

S. Mohammad E. Hosseini-Nasab  Masoumeh Vakili 《统计学通讯:理论与方法》2013,42(17):3053-3064

The magnitude of light intensity of many stars varies over time in a periodic way. Therefore, estimation of period and making inference about this parameter are of great interest in astronomy. The periodogram can be used to estimate period, properly. Bootstrap confidence intervals for period suggested here, are based on using the periodogram and constructed by percentile-t methods. We prove that the equal-tailed percentile-t bootstrap confidence intervals for period have an error of order n ^?1. We also show that the symmetric percentile-t bootstrap confidence intervals reduce the error to order n ^?2, and hence have a better performance. Finally, we assess the theoretical results by conducting a simulation study, compare the results with the coverages of percentile bootstrap confidence intervals for period and then analyze a real data set related to the eclipsing system R Canis Majoris collected by Shiraz Biruni Observatory.  相似文献   

    

David E. Giles  Hui Feng  Ryan T. Godwin 《统计学通讯:理论与方法》2013,42(11):1934-1950

The Lomax (Pareto II) distribution has found wide application in a variety of fields. We analyze the second-order bias of the maximum likelihood estimators of its parameters for finite sample sizes, and show that this bias is positive. We derive an analytic bias correction which reduces the percentage bias of these estimators by one or two orders of magnitude, while simultaneously reducing relative mean squared error. Our simulations show that this performance is very similar to that of a parametric bootstrap correction based on a linear bias function. Three examples with actual data illustrate the application of our bias correction.  相似文献   

    

Ralph C. Ward  Leonard Egede  Viswanathan Ramakrishnan  Lewis Frey  Robert Neal Axon  Clara Libby E. Dismuke 《统计学通讯:理论与方法》2013,42(18):4642-4655

Abstract

Research involving administrative healthcare data to study patient outcomes requires the investigator to account for the patient’s disease burden in order to reduce the potential for biased results. Here we develop a comorbidity summary score based on variable importance measures derived from several statistical and machine learning methods and show it has superior predictive performance to the Elixhauser and Charlson indices when used to predict 1-year, 5-year, and 10-year mortality. We used two large Veterans Administration cohorts to develop and validate the summary score and compared predictive performance using the area under ROC curve (AUC) and the Brier score.  相似文献   

    

R.L. Streit  Luginbuhl T. E 《统计学通讯:理论与方法》2013,42(12):2927-2944

Homoscedastic and heteroscedastic Gaussian mixtures differ in the constraints placed on the covariance matrices of the mixture components. A new mixture, called herein a strophoscedastic mixture, is defined by a new constraint, This constraint requires the matrices to be identical under orthogonal trans¬formations, where different transformations are allowed for different matrices. It is shown that the M-step of the EM method for estimating the parameters of strophoscedastic mixtures from sample data is explicitly solvable using singular value decompositions. Consequently, the EM-based maximum likelihood estimation algorithm is as easily implemented for strophoscedastic mixtures as it is for homoscedastic and heteroscedastic mixtures. An example of a “noisy” Archimedian spiral is presented.  相似文献   

    

Dale J. Poirier  Mario D. Tello  Stanley E. Zin 《商业与经济统计学杂志》2013,31(3):359-373

This article develops the locally uniformly most powerful unbiased Lagrange multiplier test of normality of regression disturbances within the family of power exponential distributions. The small sample power properties of the test are compared in a Monte Carlo study with 6 well-known tests across 12 alternative nonnormal distributions. In addition, the finite sample power properties for nonnormal alternatives within the power exponential family are summarized by estimating response surfaces. The results suggest that the proposed text is computationally convenient and possesses relatively attractive power properties even against alternatives outside the power exponential family.  相似文献   

    

James E. Pustejovsky  Elizabeth Tipton 《商业与经济统计学杂志》2013,31(4):672-683

ABSTRACT

In panel data models and other regressions with unobserved effects, fixed effects estimation is often paired with cluster-robust variance estimation (CRVE) to account for heteroscedasticity and un-modeled dependence among the errors. Although asymptotically consistent, CRVE can be biased downward when the number of clusters is small, leading to hypothesis tests with rejection rates that are too high. More accurate tests can be constructed using bias-reduced linearization (BRL), which corrects the CRVE based on a working model, in conjunction with a Satterthwaite approximation for t-tests. We propose a generalization of BRL that can be applied in models with arbitrary sets of fixed effects, where the original BRL method is undefined, and describe how to apply the method when the regression is estimated after absorbing the fixed effects. We also propose a small-sample test for multiple-parameter hypotheses, which generalizes the Satterthwaite approximation for t-tests. In simulations covering a wide range of scenarios, we find that the conventional cluster-robust Wald test can severely over-reject while the proposed small-sample test maintains Type I error close to nominal levels. The proposed methods are implemented in an R package called clubSandwich. This article has online supplementary materials.  相似文献