Sallie Keller
Virginia Tech
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Publication
Featured researches published by Sallie Keller.
The American Statistician | 2018
Kathryn Schaefer Ziemer; Bianica Pires; Vicki Lancaster; Sallie Keller; Mark G. Orr; Stephanie Shipp
ABSTRACT The combination of log-linear models and correspondence analysis have long been used to decompose contingency tables and aid in their interpretation. Until now, this approach has not been applied to the education Statewide Longitudinal Data System (SLDS), which contains administrative school data at the student level. While some research has been conducted using the SLDS, its primary use is for state education administrative reporting. This article uses the combination of log-linear models and correspondence analysis to gain insight into high school dropouts in two discrete regions in Kentucky, Appalachia and non-Appalachia, defined by the American Community Survey. The individual student records from the SLDS were categorized into one of the two regions and a log-linear model was used to identify the interactions between the demographic characteristics and the dropout categories, push-out and pull-out. Correspondence analysis was then used to visualize the interactions with the expanded push-out categories, boredom, course selection, expulsion, failing grade, teacher conflict, and pull-out categories, employment, family problems, illness, marriage, and pregnancy to provide insights into the regional differences. In this article, we demonstrate that correspondence analysis can extend the insights gained from SDLS data and provide new perspectives on dropouts. Supplementary materials for this article are available online.
Environmental Modelling and Software | 2018
Bianica Pires; Gizem Korkmaz; Katherine B. Ensor; David Higdon; Sallie Keller; Bryan Lewis; Aaron Schroeder
Abstract There is ample evidence that short-term ozone exposure is associated with increased respiratory symptoms. Many studies, however, aggregate the population, activities, or concentration levels of the pollutant across space and/or time, failing to capture critical variations in the exposure levels. We couple spatiotemporal air quality estimates of ozone with a synthetic information model of the Houston Metropolitan Area, allowing us to attach exposure levels to individuals based on exact times, geo-locations, and microenvironments of activities. Several scenarios of the model are run at different levels of resolution. When we maintain the spatiotemporal resolution of the data, the proportion of the population that experiences sharp increases in short-term exposure increases substantially. This can be particularly important if experienced by sensitive populations given the increased risk for adverse health effects. We find that individuals in the same zip code, neighborhood, and even household have varying levels of exposure.
Significance | 2012
Sallie Keller; S. E. Koonin; Stephanie Shipp
Annual Review of Statistics and Its Application | 2017
Sallie Keller; Gizem Korkmaz; Mark G. Orr; Aaron Schroeder; Stephanie Shipp
Annual Review of Statistics and Its Application | 2016
Sallie Keller; Stephanie Shipp; Aaron Schroeder
Statistics and Public Policy | 2017
Sallie Keller; Vicki Lancaster; Stephanie Shipp
advances in social networks analysis and mining | 2018
Gizem Korkmaz; Claire Kelling; Carol Robbins; Sallie Keller
Wiley Interdisciplinary Reviews: Computational Statistics | 2018
Sallie Keller; Stephanie Shipp; Gizem Korkmaz; Emily Molfino; Joshua Goldstein; Vicki Lancaster; Bianica Pires; David Higdon; Daniel Chen; Aaron Schroeder
Statistical journal of the IAOS | 2018
Bianica Pires; Ian Crandell; Madison Arnsbarger; Vicki Lancaster; Aaron Schroeder; Stephanie Shipp; Wendy Kang; Paula Robinson; Sallie Keller
Cityscape | 2017
Emily Molfino; Gizem Korkmaz; Sallie Keller; Aaron Schroeder; Stephanie Shipp; Daniel H. Weinberg