Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

Attenuating Initial Beliefs: Increasing the Acceptance of Anthropogenic Climate Change Information by Reflecting on Values

Anthropogenic climate change information tends to be interpreted against the backdrop of initial environmental beliefs, which can lead to some people being resistant toward the information. In this article (N = 88), we examined whether self‐affirmation via reflection on personally important values could attenuate the impact of initial beliefs on the acceptance of anthropogenic climate change evidence. Our findings showed that initial beliefs about the human impact on ecological stability influenced the acceptance of information only among nonaffirmed participants. Self‐affirmed participants who were initially resistant toward the information showed stronger beliefs in the existence of climate change risks and greater acknowledgment that individual efficacy has a role to play in reducing climate change risks than did their nonaffirmed counterparts.     

Setting tolerance limits for statistical project control using earned value management

Project control has been a research topic since decades that attracts both academics and practitioners. Project control systems indicate the direction of change in preliminary planning variables compared with actual performance. In case their current project performance deviates from the planned performance, a warning is indicated by the system in order to take corrective actions.Earned value management/earned schedule (EVM/ES) systems have played a central role in project control, and provide straightforward key performance metrics that measure the deviations between planned and actual performance in terms of time and cost. In this paper, a new statistical project control procedure sets tolerance limits to improve the discriminative power between progress situations that are either statistically likely or less likely to occur under the project baseline schedule. In this research, the tolerance limits are derived from subjective estimates for the activity durations of the project. Using the existing and commonly known EVM/ES metrics, the resulting project control charts will have an improved ability to trigger actions when variation in a project׳s progress exceeds certain predefined thresholdsA computational experiment has been set up to test the ability of these statistical project control charts to discriminate between variations that are either acceptable or unacceptable in the duration of the individual activities. The computational experiments compare the use of statistical tolerance limits with traditional earned value management thresholds and validate their power to report warning signals when projects tend to deviate significantly from the baseline schedule.     

Quality and Reliability in Top-event Estimation: Quantitative Fault Tree Analysis in Case of Dependent Events

This article deals with the quantitative Fault Tree Analysis (FTA) and the estimation method of the top-event in case of dependent events. It aims at addressing two main issues: (1) the decomposition of variability for the top-event according to several error components linked to the estimation of the top-event and sources of internal and external variations for a complex system; and (2) the definition of a Performance Measure Independent of Adjustment in order to set the quality of the top-event as a complex measure of the system failure. A simulated study applied to the health system is also carried out.     

大学生爱情非理性信念的探索性研究

采用自编问卷对300名大学生就爱情非理性信念进行了调查与分析。结果表明,当前大学生的爱情非理性信念主要表现在六个方面,即：＂消极评价＂、＂不合理期望＂、＂追求完美＂、＂错误动机＂、＂歪曲认知＂、＂绝对化自我要求＂。并且,不同性别、年级、学科、生源地的大学生表现出不同的爱情非理性信念特点。     

Gambling motivations and superstitious beliefs: a cross-cultural study with casino customers

The expansion of legalized commercial gaming in Macau has motivated stakeholders to explore opportunities in other Asian countries. However, there is a lack of research focusing on casino customers in these markets. Thus, the purpose of this study is to explore gambling superstitious beliefs and motivations of those visiting a casino in South Korea, and how these factors are different across four ethnic groups. The researchers surveyed 323 casino customers in the lounge area on the casino floor, including Americans, Chinese, Japanese, and Koreans living abroad. This study found American gamblers could be characterized as more superstitious than Japanese gamblers, while the Chinese and American gamblers exhibited many similarities regarding the pattern of superstitious beliefs that they were most likely to endorse. The findings also suggest the culture and the area around the casino might be more important to Chinese, while novelty to Japanese and winning money to Korean gamblers are seen as most important. This study contributes to gambling literature by examining gamblers’ beliefs and motives in a different setting with more diverse populations than those in previous studies. The findings of this study will help casino operators properly develop and adjust strategies to thrive in the Asian marketplace.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Replication: Revisiting Tversky and Shafir’s (1992) Disjunction Effect with an extension comparing between and within subject designs

Does uncertainty about an outcome influence decisions? The sure-thing principle (Savage, 1954) posits that it should not, but Tversky and Shafir (1992) found that people regularly violate it in hypothetical gambling and vacation decisions, a phenomenon they termed “disjunction effect”. Very close replications and extensions of Tversky and Shafir (1992) were conducted in this paper (N = 890, MTurk). The target article demonstrated the effect using two paradigms in a between-subject design: here, an extension also testing a within-subject design, with design being randomly assigned was added. These results were consistent with the original findings for the “paying to know“ problem (original: Cramer’s V = 0.22, 95% (CI) [0.14, 0.32]; replication: Cramer’s V = 0.30, 95% CI [0.24, 0.37]), yet not for the “choice under risk” problem (original: Cramer’s V = 0.26, 95% CI [0.14, 0.39]; replication: Cramer’s V = 0.11, 95% CI [−0.07, 0.20]). The within-subject extension showed very similar results. Implications for the disjunction effect and judgment and decision-making theory are discussed, and a call for improvements on the statistical understanding of comparisons of between-subject and within-subject designs is introduced. All materials, data, and code are available on https://osf.io/gu58m/.     

The Aversion to Tampering with Nature (ATN) Scale: Individual Differences in (Dis)comfort with Altering the Natural World

People differ in their comfort with tampering with the natural world. Although some see altering nature as a sign of human progress, others see it as dangerous or hubristic. Across four studies, we investigate discomfort with tampering with the natural world. To do so, we develop the Aversion to Tampering with Nature (ATN) Scale, a short scale that is the first to directly measure this discomfort. We identify six activities that people believe tamper with nature (geoengineering, genetically modified organisms, pesticides, cloning, gene therapy, and nanoparticles) and show that ATN scores are associated with opposition to these activities. Furthermore, the ATN Scale predicts actual behavior: donations to an anti-tampering cause. We demonstrate that ATN is related to previously identified constructs including trust in technology, naturalness bias, purity values, disgust sensitivity, aversion to playing God, and environmental beliefs and values. By illuminating who is concerned about tampering with nature and what predicts these beliefs, the ATN Scale provides opportunities to better understand public opposition to technological innovations, consumer preferences for “natural” products, and strategies for science communication.