Non-parametric estimation of lifetime distribution of competing risk models when censoring times are missing

There are situations in the analysis of failure time or lifetime data where the censoring times of unfailed units are missing. The non-parametric estimator of the lifetime distribution for such data is available in literature. In this paper we consider an extension of this situation to the univariate and bivariate competing risk setups. The maximum likelihood and simple moment estimators of cause specific distribution functions in both univariate and bivariate situations are developed. A simulation study is carried out to assess the performance of the estimators. Finally, we illustrate the method with real data set.     

Accident Epidemiology and the U.S. Chemical Industry: Accident History and Worst-Case Data from RMP*Info

This article reports on the data collected on one of the most ambitious government-sponsored environmental data acquisition projects of all time, the Risk Management Plan (RMP) data collected under section 112(r) of the Clean Air Act Amendments of 1990. This RMP Rule 112(r) was triggered by the Bhopal accident in 1984 and led to the requirement that each qualifying facility develop and file with the U.S. Environmental Protection Agency a Risk Management Plan (RMP) as well as accident history data for the five-year period preceding the filing of the RMP. These data were collected in 1999-2001 on more than 15,000 facilities in the United States that store or use listed toxic or flammable chemicals believed to be a hazard to the environment or to human health of facility employees or off-site residents of host communities. The resulting database, RMP*Info, has become a key resource for regulators and researchers concerned with the frequency and severity of accidents, and the underlying facility-specific factors that are statistically associated with accident and injury rates. This article analyzes which facilities actually filed under the Rule and presents results on accident frequencies and severities available from the RMP*Info database. This article also presents summaries of related results from RMP*Info on Offsite Consequence Analysis (OCA), an analytical estimate of the potential consequences of hypothetical worst-case and alternative accidental releases on the public and environment around the facility. The OCA data have become a key input in the evaluation of site security assessment and mitigation policies for both government planners as well as facility managers and their insurers. Following the survey of the RMP*Info data, we discuss the rich set of policy decisions that may be informed by research based on these data.     

Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias

Benzene is classified as a group 1 human carcinogen by the International Agency for Research on Cancer, and it is now accepted that occupational exposure is associated with an increased risk of various leukaemias. However, occupational exposure accounts for less than 1% of all benzene exposures, the major sources being cigarette smoking and vehicle exhaust emissions. Whether such low level exposures to environmental benzene are also associated with the risk of leukaemia is currently not known. In this study, we investigate the relationship between benzene emissions arising from outdoor sources (predominantly road traffic and petrol stations) and the incidence of childhood leukaemia in Greater London. An ecological design was used because of the rarity of the disease, the difficulty of obtaining individual level measurements of benzene exposure and the availability of data. However, some methodological difficulties were encountered, including problems of case registration errors, the choice of geographical areas for analysis, exposure measurement errors and ecological bias. We use a Bayesian hierarchical modelling framework to address these issues, and we investigate the sensitivity of our inference to various modelling assumptions.     

Immigrant wage differentials, ethnicity and occupational segregation

Summary.  We investigate occupational attainment as well as estimating earnings differentials for non-white migrants and non-white natives, including occupational effects. We control for the occupational selection of immigrants and compare across native and immigrant groups. Relative to white natives, we find no evidence of an ethnic pay disadvantage for white and South Asian professional workers. Although occupational segregation and other human capital and socio-economic factors provide a partial explanation for the raw earnings differential, evidence of ethnic-based disadvantage in most occupations persists.     

O(m2) ALGORITHMS FOR THE TWO AND THREE SUBLOT LOT STREAMING PROBLEM

Lot streaming is the process of splitting a job or lot into sublots to reduce its makespan on a sequence of machines. The goal in the lot streaming problem is to find the optimal size of each sublot that will minimize the makespan. The makespan is defined as the time the last sublot completes its processing on the last machine. If the sizes of these sublots are restricted to remain the same on all machines, the solution is called a consistent sublot solution. However, if the sizes of the sublots are allowed to vary, the solution is referred to as a nonconsistent or variable sublot solution. Also, if the machines must be in operation continuously from the first to the last sublot, the solution is a no idling solution. When setups are explicitly considered in the problem, there will be two cases. If setups on each machine require some portion of the first sublot be present by the machine, the problem is referred to as the attached setup time problem. If setups can be performed ahead of time before the first sublot reaches the particular machine, the corresponding problem is referred to as the detached setup problem. Finally, if the machines are allowed to be idle between the processing of sublots, the resultant solution is an intermittent idling solution. In this paper, the consistent sublot lot streaming problem with intermittent idling and no setups is discussed. The models developed also assume that the number of sublots are fixed and known. The m machine two sublot lot streaming problem is reviewed. An algorithm for the three sublot, m machine problem is derived using a network representation of the problem. The complexity of the algorithm is O (m²). Finally, using the insights from three sublot problem, a heuristic algorithm is provided for the m machine, n sublot problems. The results on the proposed heuristic are very encouraging; average percent deviation from optimal makespan is approximately at 0.76% on 155 randomly generated problems with different m and n values.     

Increasing the Effectiveness of Student Evaluation of Instructor Data through a Factor Score Comparative Report

Effective student evaluation of instructor instruments must provide norm, or comparative, data to aid interpretation. This note highlights an innovative factor score comparative report. Rather than merely reporting comparative data on individual questions items, the innovative report provides comparative percentile data on the six factors underlying our thirty-three item questionnaire. The faculty indicated overwhelming support for the new report. The note also briefly mentions three other activities that are essential for student evaluation of instructor data to improve teacher effectiveness. Our goal is to stimulate other colleges to adopt the innovative norming practice once they have validated their local evaluation instruments. College-wide improvement of teaching will occur through such do-it-yourself efforts and only decision science faculty are technically qualified to lead such efforts.