A Bayesian Approach for Analyzing Results of Vehicle Collision Tests

Certain motor vehicle safety standards stipulate a collision test speed and a set of performance criteria that vehicles must satisfy during or after the collision test. For example, Federal Motor Vehicle Safety Standard 301 requires a 30 mile per hour (mph) barrier collision and specifies a certain maximum allowable limit on the total spillage of fuel. Vehicle designs are required to meet this standard; however, when collision tests are conducted at speeds higher than the standard, vehicles do not always satisfy the performance criteria. This paper develops a mathematical model for estimating the probability of meeting the standard by using a Bayesian framework to incorporate engineering judgment with collision test results. The model is based on the idea that there are random features to a vehicle's ability to meet performance standards in a collision, especially at such elevated speeds. Example calculations are included to illustrate the estimation of the probability of meeting the standard and to compare it with a maximum likelihood approach.     

On the Joint Lot-Sizing Problem with Zero Setup Costs

In a recent paper, Pinto and Mabert [5] presented a lot-sizing rule and an improvement procedure for the joint lot-sizing problem with zero setup costs. We show that this procedure often yields infeasible schedules. We also present and discuss two interesting properties of the joint lot-sizing problem with zero setup costs. A numerical example to illustrate the second property is provided.     

Data Driven Modeling: An Application in Scheduling

This paper presents a data driven modeling (DDM) approach to certain types of optimization problems. DDM relinquishes control of the completed model to the user department rather than the operations research (OR) staff. The approach emphasizes development of models that are dependent on data maintained and understood by the users. The data base consists of coded user rules which describe when changes will occur in the problem structure and data which captures the generalization of the problem. Both the rules and data can be updated by user department personnel. These data drive a matrix generator controlled by the rules which uses the data base as input to generate the specific model formulation. This DDM system is designed by OR consultants or staff to allow independence of use along with low-cost and minimal-effort maintenance. The DDM approach is illustrated with an application to a real-world medical scheduling problem.     

Cleaning Up Water? Or Building Rural Community? Community Watershed Organizations in Pennsylvania*

Abstract Recent initiatives from state and federal government agencies have helped foster the formation of community‐based watershed organizations. Although there is a great deal of enthusiasm about the potential of these organizations to enhance water quality, relatively little attention has been paid to the impacts these organizations may have on the well‐being of rural communities more generally. Assessments of effectiveness have typically focused on specific activities and accomplishments, rather than a broader range of community‐based effects. In short, we ask whether community‐based environmental management improves community as well as environment. Our research utilized a mixed‐methods design, including a statewide mail survey of all Pennsylvania watershed organizations, followed by in‐depth interviews with 28 rural watershed organizations. This sequential approach progressively explored in more detail definitions of effectiveness, including the building of rural capacity. We find watershed organizations are potentially effective mechanisms for building local leadership, enhancing the skills of rural residents, and making valuable connections with other communities, facing similar water‐resource and rural‐development issues. However, the range of issues with which local watershed organizations engage and the methods they currently utilize may eventually limit their usefulness.     

An Empirical Examination of Characteristics of Mexican Migrants to Metropolitan and Nonmetropolitan Areas of the United States*

Abstract This research examines differences between those Mexican migrants choosing metropolitan destinations and those choosing destinations outside metropolitan areas of the United States. Using general estimating equations, the study presents data indicating that since the 1960s migrants choosing rural destinations are less fluent in English, slightly older, much less educated, far more likely to be unskilled, more likely to be married, and more likely to be undocumented. The picture is more complex when consideration is restricted to those migrants arriving in rural areas since the passage of the North American Free Trade Agreement. These migrants are far more likely to be single, have more education but have less English fluency, have less work experience, and have less family experience with migration to the United States. They are more likely to come from small towns and rural areas of Mexico.     

Social Background Differences in Early Family Behavior

Social background has historically been recognized as a major factor influencing family behavior, though recent work has largely emphasized racial/ethnic influences. Here we use 1994 – 1995 and 2001 – 2002 Add Health data to examine the cohabitation, first marriage, and first birth experience of young women. In a multistate life table context, hypothetical cohorts specified in terms of race and mother’s education are followed, from age 11 to age 24, as they move through 6 family‐related statuses. The results indicate that, for both Black and White women, a higher level of maternal education is generally associated with less cohabitation, less marriage, fewer first births, and a higher percentage of women who experience none of those transitions before age 24. Racial and social background differences are conceptually and empirically distinct. Because mother’s education is associated with substantially different trajectories of early family behavior for both Blacks and Whites, we argue that social background merits increased attention in research on contemporary American family patterns.     

Using conceptual models as a planning and evaluation tool in conservation

Conservation projects are dynamic interventions that occur in complex contexts involving intricate interactions of social, political, economic, cultural, and environmental factors. These factors are constantly changing over time and space as managers learn more about the context within which they work. This complex context poses challenges for planning and evaluating conservation project. In order for conservation managers and evaluation professionals to design good interventions and measure project success, they simultaneously need to embrace and deconstruct contextual complexity.In this article, we describe conceptual models—a tool that helps articulate and make explicit assumptions about a project's context and what a project team hopes to achieve. We provide real-world examples of conceptual models, discuss the relationship between conceptual models and other evaluation tools, and describe various ways that conceptual models serve as a key planning and evaluation tool. These include, for example, that they document assumptions about a project site and they provide a basis for analyzing theories of change.It is impractical to believe that we can completely eliminate detail or dynamic complexity in projects. Nevertheless, conceptual models can help reduce the effects of this complexity by helping us understand it.     

Temporal Patterns of Accuracy Confidence in Social Judgments: A New Method and Initial Results

An integrated, computer-based system was developed to record participants’ continuous judgment changes on a revised form of the Interpersonal Perception Task (IPT-15). Consistent with the considerable research on “thin slice” judgments, the mean latency for greater than chance accuracy confidence was just 16 s (median = 10 s) for the ten one-part scenes on the IPT. There was also a clear and strong linear trend for increasing accuracy confidence across the first 25 s of the ten one-part scenes. For the five-two-part scenes, where comparative judgments were required (e.g., which statement is truthful, which is a lie?), no clear pattern of increasing accuracy confidence was found, with mean scores hovering near chance. The utility of the new system for analyzing the time course of social judgments is discussed and the potential reasons for the contrasting results for the one-part and two-part scenes were examined.     

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model. For a long time, however, likelihood-based estimation was only feasible for ERG models assuming dyad independence. For more realistic and complex models inference has been based on the pseudo-likelihood. Recent advances in computational methods have made likelihood-based inference practical, and comparison of the different estimators possible.     

Former Minister Zhang's discourse on SARS: Government's image restoration or destruction?

This study analyzes the image repair discourse by Chinese Health Minister Zhang Wenkang's discourse on SARS. The minister faced several accusations: the SARS outbreak was growing, the Chinese government had covered up the severity of this problem, the Chinese government ignored Taiwanese who suffered from SARS, and the Health Ministry provided information that was neither timely nor accurate. He employed several image repair strategies (denial, defeasibility, bolstering, minimization, differentiation, attack accuser, and corrective action). However, his messages were contradictory and apparently related on false information, so his efforts were unsuccessful and he was stripped of his office.