Pires B, Korkmaz G, Ensor K, Higdon D, Keller S, Lewis B, Schroeder A. Estimating Individualized Exposure Impacts from Ambient Ozone Levels: A Synthetic Information Approach. Environmental Modelling & Software. 2018;103:146–157.
Keller S, Shipp S, Korkmaz G, Molfino E, Goldstein J, Lancaster V, Pires B, Higdon D, Chen D, Schroeder A. Harnessing the power of data to support community-based research. WIREs Computational Statistics. 2018:e1426.
Pires B, Goldstein J, Higdon D, Sabin P, Korkmaz G, Shipp S, Keller S, Ba S, Hamall K, Koehler A, Reese S. A Bayesian simulation approach for supply chain synchronization. In: Proceedings of the 2017 Winter Simulation Conference. IEEE; 2018:1571–1582. https://doi.org/10.1109/WSC.2017.8247898.
Wulczyn F, Clinch R, Coulton C, Keller S, Moore J, Muschkin C, Nicklin A, LeBoeuf W, Barghaus K. Establishing a Standard Data Model for Large-Scale IDS Use. Actionable Intelligence for Social Policy, University of Pennsylvania; 2017.
Keller S, Korkmaz G, Orr M, Schroeder A, Shipp S. The Evolution of Data Quality: Understanding the Transdisciplinary Origins of Data Quality Concepts and Approaches. Annual Review of Statistics and its Application, Vof 4. 2017;4:85–108. https://doi.org/10.1146/annurev-statistics-060116-054114.
Keller S, Shipp S, Orr M, Higdon D, Korkmaz G, Schroeder A, Molfino E, Pires B, Ziemer K, Weinberg DH. Leveraging External Data Sources to Enhance Official Statistics and Products. Report Prepared for the U.S. Census Bureau. 2016.
Pires B, Korkmaz G, Ensor K, Higdon D, Keller S, Lewis B, Schroeder A. Towards an in silico Experimental Platform for Air Quality: Houston, TX as a Case Study. Presented at the Annual Conference of the Computational Social Science Society of the Americas (CSSSA), Santa Fe, New Mexico; 2015. http://computationalsocialscience.org/wp-content/uploads/2015/10....
Keller S, Shipp S. Building Resilient Cities: Harnessing the Power of Urban Analytics in The Resilience Challenge: Looking at Resilience through Multiple Lens. Charles C. Thomas Ltd Publishers; 2015.
Orr MG, Lewis B, Ziemer K, Keller S. Search Health Topics Health Care Delivery. Issues. 2015;2013.
Bisgaard S, Doganaksoy N, Fisher N, Gunter B, Hahn G, Keller-McNulty S, Kettenring J, Meeker WQ, Montgomery DC, Wu CFJ. The Future of Industrial Statistics: A Panel Discussion. Technometrics. 2008;50(2):103–127. https://doi.org/10.1198/004017008000000136.
Keller-McNulty S. From Data to Policy: Scientific Excellence Is Our Future. Journal of the American Statistical Association. 2007;102:395–399. https://doi.org/10.2307/27639871.
Williams B, Higdon D, Gattiker J, Moore L, McKay M, Keller-McNulty S. Combining experimental data and computer simulations, with an application to flyer plate experiments. Bayesian Analysis. 2006;1(4):765–792. https://doi.org/10.1214/06-BA125.
Keller-McNulty S, Bellman KL, Carley KM, Davis PK, Ivanetich R, Laskey KB. Defense Modeling, Simulation, and Analysis: Meeting the Challenge. 2006.
Keller-McNulty S, Wilson AG. Reliability for the 21st century. Mathematical Methods in Reliability. 2004;1.
Higdon D, Williams B, Moore L, McKay M, Keller-McNulty S. Uncertainty quantification for combining experimental data and computer simulations. 2004.
Bennett TR, Booker JM, Keller-McNulty S, Singpurwalla ND. Testing the untestable: reliability in the 21st century. IEEE Transactions on Reliability. 2003;52(1):118–124. https://doi.org/10.1109/TR.2002.807239.
Berk RA, Bickel P, Campbell K, Fovell R, Keller-McNulty S, Kelly E, Linn R, Park B, Perelson A, Rouphail N, Sacks J, Schoenberg F. Workshop on Statistical Approaches for the Evaluation of Complex Computer Models. Statistical Science. 2002;17:173–192. https://doi.org/10.2307/3182823.
Duncan GT, Keller-McNulty SA, Stokes SL. Disclosure Risk vs. Data Utility: The RU Confidentiality Map. Citeseer; 2001.
Keller-McNulty S, Duncan G. Disclosure-Limited Statistical Analysis for Confidential Data to Support NSF-Sponsored Digital Government Grant. 2001.
Meyer M, Keller McNulty S, Bement T, Booker J, McNulty M, Singpurwalla N. PREDICT. 2001.
Keller-McNulty S, McNulty M. Show Me the Data: Statistical Representation. Theoria et Historia Scientarum Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the University of California for the US Department of Energy under contract W-7405-ENG-36 By acceptance of this article, the publisher recognizes that the US Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or to allow others to do so, for US Government purposes Los Alamos National Laboratory requests that the publisher identify this article as work performed under the auspices of the US Department of Energy Los Alamos National Laboratory strongly supports academic freedom and a researcher’s right to publish; as an institution, however, the Laboratory does not endorse the viewpoint of a publication or guarantee its technical correctness FORM 836 (10/96). 2000:2–2. https://doi.org/10.12775/ths.2002.023. .
Chen G, Keller-McNulty S. Estimation of identification disclosure risk in microdata. Journal of Official Statistics. 1998;14(1):79–95.
Keller-McNulty S, Unger EA. A Remote Access Database System Prototype for the Release of Confidential Data. Journal of Official Statistics. 1998;14(4):346–360.
Keller-McNulty S. A numerical analysis approach to the teaching of statistical computing. In: Proceedings of the Seventeenth Symposium on the Interface of Computer Sciences and Statistics on Computer Science and Statistics. Elsevier North-Holland, Inc.; 1996:137–140.
Keller-McNulty S. [Enhancing Access to Microdata While Protecting Confidentiality: Prospects for the Future]: Comment. Statistical Science. 1991;6(3):234–235. https://doi.org/10.1214/ss/1177011683.
Unger EA, Keller McNulty S, Connelly P. Natural change in dynamic databases as a deterrent to compromise by trackers. In: Proceedings of the Sixth Annual Computer Security Applications Conference, 1990. IEEE; 1990:116–124.
Keller-McNulty S, Unger EA. The Deterrent Value of Natural Change in a Statistical Database. In: Proceedings of the Statistical Computing Section, American Statistical Association. 1990:15–23.
Keller McNulty S, McNulty M, Unger EA. The Protection of Confidential Data. In: Proceedings of the 21st Symposium on the Interface of Computer Science and Statistics. 1989.
Unger EA, Keller McNulty S. Modeling Parallelism: An Interdisciplinary Approach. In: Proceedings of the 20th Symposium on the Interface of Computer Science and Statistics. 1988.
Keller-Mcnulty A, Higgins JJ. Effect of tail weight and outliers on power and type-i error of robust permutation tests for location. Communications in Statistics - Simulation and Computation. 1987;16(1):17–35. https://doi.org/10.1080/03610918708812575.
Keller-McNulty S, Kennedy WJ. Error-free computation of the moore-penrose inverse with application to linear least squares analysis. Journal of Statistical Computation and Simulation. 1987;27(1):45–64. https://doi.org/10.1080/00949658708810979.
Keller-McNulty S, ennedy WJ. An error-free generalized matrix inversion and linear least squares method based on bordering. Communications in Statistics - Simulation and Computation. 1986;15(3):769–785. https://doi.org/10.1080/03610918608812539.
Keller McNulty S, Kennedy WJ. Error-Free Computation of a Reflexive Generalized Inverse. Linear Algebra and Its Applications. 1985;67:157–167.