11,328 research outputs found

    Musselman Display Case

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    The Gettysburg College campus without the influence of the Musselman family would be a very different place. The Musselman name is not one that can be easily overlooked on campus, as numerous buildings are named after the famous apple processing family located in Biglerville, Pa. Yet without the generosity of the Musselman and the Emma G. Musselman foundation, the college would not only be lacking Musselman Stadium, Musselman Hall, and Musselman Library, but also the Bream Wright Hauser Field House, and thousands of dollars in scholarships awarded to students over the past several years. The Musselmans have undoubtedly left a strong imprint on the college and the greater community, and their charity has touched a countless number of people. Within the Musselman Library there is a display case devoted to the family, without whom the library itself would cease to exist. Inside this display, there are several photographs exploring the history and legacy of this remarkable family, and paying tribute to those who have brought so much to Gettysburg College. [excerpt] Course Information: Course Title: HIST 300: Historical Method Academic Term: Spring 2006 Course Instructor: Dr. Michael J. Birkner \u2772 Hidden in Plain Sight is a collection of student papers on objects that are hidden in plain sight around the Gettysburg College campus. Topics range from the Glatfelter Hall gargoyles to the statue of Eisenhower and from historical markers to athletic accomplishments. You can download the paper in pdf format and click View Photo to see the image in greater detail.https://cupola.gettysburg.edu/hiddenpapers/1028/thumbnail.jp

    User guide for WIACX: A transonic wind-tunnel wall interference assessment and correction procedure for the NTF

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    A three dimensional transonic Wind-tunnel Interference Assessment and Correction (WIAC) procedure developed specifically for use in the National Transonic Facility (NTF) at NASA Langley Research Center is discussed. This report is a user manual for the codes comprising the correction procedure. It also includes listings of sample procedures and input files for running a sample case and plotting the results

    Vindicating Bankruptcy Rights

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    Robust and Flexible Estimation of Stochastic Mediation Effects: A Proposed Method and Example in a Randomized Trial Setting

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    Causal mediation analysis can improve understanding of the mechanisms underlying epidemiologic associations. However, the utility of natural direct and indirect effect estimation has been limited by the assumption of no confounder of the mediator-outcome relationship that is affected by prior exposure---an assumption frequently violated in practice. We build on recent work that identified alternative estimands that do not require this assumption and propose a flexible and double robust semiparametric targeted minimum loss-based estimator for data-dependent stochastic direct and indirect effects. The proposed method treats the intermediate confounder affected by prior exposure as a time-varying confounder and intervenes stochastically on the mediator using a distribution which conditions on baseline covariates and marginalizes over the intermediate confounder. In addition, we assume the stochastic intervention is given, conditional on observed data, which results in a simpler estimator and weaker identification assumptions. We demonstrate the estimator's finite sample and robustness properties in a simple simulation study. We apply the method to an example from the Moving to Opportunity experiment. In this application, randomization to receive a housing voucher is the treatment/instrument that influenced moving to a low-poverty neighborhood, which is the intermediate confounder. We estimate the data-dependent stochastic direct effect of randomization to the voucher group on adolescent marijuana use not mediated by change in school district and the stochastic indirect effect mediated by change in school district. We find no evidence of mediation. Our estimator is easy to implement in standard statistical software, and we provide annotated R code to further lower implementation barriers.Comment: 24 pages, 2 tables, 2 figure
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