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In studies involving subclinical events, times of events are often subject to interval censoring since their occurrence is only detected at inspection times. When individuals are event-free at an initial time and a single follow-up inspection is made, current status data are obtained. In many settings, however, the population comprised a susceptible and a nonsusceptible subpopulation, where only susceptible individuals will go on to experience the event. Then interest often lies primarily in identifying prognostic variables for susceptibility, and secondarily in the event time distribution among the susceptible individuals. We give a simple mixture model that facilitates estimation of the proportion of susceptible individuals, covariate effects on the odds of susceptibility, and the event time distribution under a current status observation scheme. Asymptotic relative efficiency of maximum likelihood estimators is considered based on the Fisher information for a variety of settings. EM algorithms are proposed for parametric, weakly parametric, and nonparametric estimation of the event time distribution. The methods are applied to motivating studies examining an immunological response to low molecular weight heparin in patients undergoing orthopedic surgery.

Statistics educators have long recognized the importance of empowering students with statistical thinking skills that could be applied beyond the classroom. However, there is a dearth of research on how students deem statistical topics as having practical future relevance after they complete introductory courses. Focusing on student interest in and perceived value of statistics, this study reports findings from a qualitative study that examined students’ written reflections to explore the nature and extent of the perceived future relevance of statistics among undergraduate students who completed a first-year introductory statistics course online. Findings show that students deemed statistics topics as important if they could be applied to their everyday lives or their academic- and career-related interests. We conclude with recommendations for instructors of introductory statistics courses that enroll students with diverse interests and goals. First published November 2018 at Statistics Education Research Journal Archives

Summary Real‐world phenomena simulation models, which can be used to engage middle‐school students with probability, are described. Links to R instructional material and easy‐to‐use code are provided to facilitate implementation in the classroom.

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