Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data.

%B Statistics in Medicine %V 31 %P 2123-2136 %G eng %0 Conference Paper %B Proceedings, American Society for Engineering Education %D 2011 %T Studying the Reliability and Validity of Test Scores for Mathematical and Spatial Reasoning Tasks for Engineering Students %A Pauley, L. %A Kulikowich, J. %A Sedransk, N. %A Engel, R. %B Proceedings, American Society for Engineering Education %G eng %0 Journal Article %J PACE %D 2011 %T Systematic decrements in QTc between the first and second day of contiguous daily ECG recordings under controlled conditions %A Beasley CM Jr %A Benson C %A Xia JQ %A Young SS %A Haber H %A Mitchell MI %A Loghin C %K ECG %K QT interval %XBACKGROUND: Many thorough QT (TQT) studies use a baseline day and double delta analysis to account for potential diurnal variation in QTc. However, little is known about systematic changes in the QTc across contiguous days when normal volunteers are brought into a controlled inpatient environment.

%B PACE %V 34 %P 1116-1127 %8 April %G eng %R doi:10.1111/j.1540-8159.2011.03117.x %0 Journal Article %J Journal of Privacy and Confidentiality %D 2010 %T Secure statistical analysis of distributed databases, emphasizing what we don’t know %A A. F. Karr %B Journal of Privacy and Confidentiality %V 1 %P 197-211 %G eng %0 Journal Article %J Journal of Official Statistics %D 2010 %T Statistical Careers in US Government Science Agencies %A Sedransk, N. %K complex system models %K engineering statistics %K high-dimensional data %K History of statistics %K metrology %XThe role of statistics in those U.S. government agencies that focus on progress in science and engineering became prominent at the end of the Second World War. The success of statistics in that historical period came from the power of statistics to enable science to advance more rapidly and with great assurance in the interpretation of experimental results. Over the past three quarters of a century, technology has changed both the practice of science and the practice of statistics. However, the comparative advantage of statistics still rests in the ability to achieve greater precision with fewer errors and a deeper understanding. Examples illustrate some of the challenges that complex science now presents to statisticians, demanding both creativity and technical skills.

%B Journal of Official Statistics %V 26 %P 443-453 %G eng %0 Journal Article %J Computer Math Organ Theory %D 2009 %T Special issue on dynamic models for social networks %A David Banks %B Computer Math Organ Theory %V 15 %P 259-260 %8 12/2009 %G eng %& 259 %R 10.1007/s10588-009-9062-6 %0 Journal Article %J Q. Applied Mathematics %D 2008 %T Sensitivity to noise variance in a social network dynamics model %A H. T. Banks %A H. K. Nguyen %A J. R. Samuels, Jr. %A A. F. Karr %B Q. Applied Mathematics %V 66 %P 233-247 %G eng %0 Book Section %B Encyclopedia of Risk Assessment IV %D 2008 %T Social Networks %A D. L. Banks %A N. Hengartner %K block models %K counterterrorism %K exponential family %K latent space models %K p* models %XSocial networks models are a body of statistical procedures for describing relationships between agents. The term stems from initial applications that studied interactions within human communities, but the methodology is now used much more broadly and can analyze interactions among genes, proteins, nations, and websites. In the context of risk analysis, social network models have been used to describe the formation, persistence, and breakdown of terrorist cells. They also pertain to studies of organizational behavior.

%B Encyclopedia of Risk Assessment IV %I Wiley %G eng %R 10.1002/9780470061596.risk0667 %0 Journal Article %J Journal of Computational Statistics and Data Analysis %D 2007 %T Secure computation with horizontally partitioned data using adaptive regression splines %A A. F. Karr %A J. Ghosh %A J. P. Reiter %XWhen several data owners possess data on different records but the same variables, known as horizontally partitioned data, the owners can improve statistical inferences by sharing their data with each other. Often, however, the owners are unwilling or unable to share because the data are confidential or proprietary. Secure computation protocols enable the owners to compute parameter estimates for some statistical models, including linear regressions, without sharing individual records’ data. A drawback to these techniques is that the model must be specified in advance of initiating the protocol, and the usual exploratory strategies for determining good-fitting models have limited usefulness since the individual records are not shared. In this paper, we present a protocol for secure adaptive regression splines that allows for flexible, semi-automatic regression modeling. This reduces the risk of model mis-specification inherent in secure computation settings. We illustrate the protocol with air pollution data.

%B Journal of Computational Statistics and Data Analysis %V 51 %P 5813-5820 %8 August %G eng %R 10.1016/j.csda.2006.10.013 %0 Conference Paper %B Bulletin of International Statistics Institute %D 2007 %T Secure logistic regression with distributed databases %A A. F. Karr %A S. E. Fienberg %A Y. Nardi %A A. Slavkovic %B Bulletin of International Statistics Institute %G eng %0 Journal Article %J Journal of Data Science %D 2007 %T Statistics in metrology: International key comparisons and interlaboratory studies %A Sedransk, N. %A Rukhin, A. %B Journal of Data Science %V 5 %P 393-412 %G eng %0 Journal Article %J Technometrics %D 2006 %T Secure, privacy-preserving analysis of distributed databases %A Alan F. Karr %A Fulp, WJ %A F. Vera %A Young, S.S. %A X. Lin %A J. P. Reiter %XThere is clear value, in both industrial and government settings, derived from performing statistical analyses that, in effect, integrate data in multiple, distributed databases. However, the barriers to actually integrating the data can be substantial or even insurmountable. Corporations may be unwilling to share proprietary databases such as chemical databases held by pharmaceutical manufacturers, government agencies are subject to laws protecting confidentiality of data subjects, and even the sheer volume of the data may preclude actual data integration. In this paper, we show how tools from modern information technology?specifically, secure multiparty computation and networking?can be used to perform statistically valid analyses of distributed databases. The common characteristic of the methods we describe is that the owners share sufficient statistics computed on the local databases in a way that protects each owner from the others. That is, while each owner can calculate the ?complement ? of its contribution to the analysis, it cannot discern which other owners contributed what to that complement. Our focus is on horizontally partitioned data: the data records rather than the data attributes are spread among the owners. We present protocols for secure regression, contingency tables, maximum likelihood and Bayesian analysis. For low-risk situations, we describe a secure data integration protocol that integrates the databases but prevents owners from learning the source of data records other than their own. Finally, we outline three current research directions: a software system implementing the protocols, secure EM algorithms, and partially trusted third parties, which reduce incentives to owners not to be honest.

%B Technometrics %V 48 %P 133-143 %G eng %R 10.1198/004017007000000209 %0 Journal Article %J Metrologia %D 2006 %T Statistical analysis for multiple artifact problem in key comparisons with linear trends %A Zhang, N.-F. %A Strawderman, W. %A Liu, H.-k. %A Sedransk, N. %K computational physics %K instrumentation and measurement %XA statistical analysis for key comparisons with linear trends and multiple artefacts is proposed. This is an extension of a previous paper for a single artefact. The approach has the advantage that it is consistent with the no-trend case. The uncertainties for the key comparison reference value and the degrees of equivalence are also provided. As an example, the approach is applied to key comparison CCEM–K2.

%B Metrologia %V 43 %P 21-26 %G eng %R 10.1088/0026-1394/43/1/003 %0 Journal Article %J Technom %D 2006 %T Statistical design of pools using optimal coverage and minimal collision %A Remlinger KS %A Hughes-Oliver JM %A Young SS %A Lam RL %K Pharmaceutical industry %K Pooled data %K Pooling %K Screening %K Throughput %XThe screening of large chemical libraries to identify new compounds can be simplified by testing compounds in pools. Two criteria for designing pools are considered: optimal coverage of the chemical space and minimal collision between compounds. Four pooling designs are applied to a public database and evaluated by determining how well the design criteria are met and whether the methods are able to find diverse active compounds. While one pool was outstanding, all designed pools outperformed randomly designed pools.

%B Technom %V 48 %P 133-143 %G eng %R 10.1198/004017005000000481 %0 Generic %D 2006 %T Survey Costs: Workshop Report and White Paper %A A. F. Karr %A M. Last %I National Institute of Statistical Sciences %G eng %0 Journal Article %J Biostatistics %D 2005 %T Sample size calculation for multiple testing in microarray data analysis %A Jung SH %A Bang H %A Young SS %B Biostatistics %V 6 %P 157-169 %G eng %0 Journal Article %J J. Computer-Aided Molecular Design %D 2005 %T Secure analysis of distributed chemical databases without data integration %A Alan F. Karr %A Jun Feng %A Xiaodong Lin %A Ashish P. Sanil %A S. Stanley Young %A Jerome P. Reiter %B J. Computer-Aided Molecular Design %V 19 %P 739-747 %8 November %G eng %0 Journal Article %J J. Computational and Graphical Statist %D 2005 %T Secure Regression on Distributed Databases %A Alan F. Karr %A Alan F. Karr %A Xiaodong Lin %A Xiaodong Lin %A Ashish P. Sanil %A Ashish P. Sanil %A Jerome P. Reiter %A Jerome P. Reiter %B J. Computational and Graphical Statist %V 14 %P 263–279 %G eng %0 Conference Paper %B In Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication %D 2005 %T Secure statistical analysis of distributed databases using partially trusted third parties. Manuscript in preparation %A Alan F. Karr %A Xiaodong Lin %A Ashish P. Sanil %A Jerome P. Reiter %E D. Olwell %E A. G.Wilson %E G. Wilson %B In Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication %I Springer–Verlag %C New York %G eng %0 Conference Paper %B Proceedings of 2004 Workshop on Verification & Validation of Computer Models of High-consequence Engineering Systems %D 2005 %T A statistical meteorologist looks at computational system models %A Sedransk, N. %B Proceedings of 2004 Workshop on Verification & Validation of Computer Models of High-consequence Engineering Systems %G eng %0 Conference Paper %B ASA Proceedings 2004 %D 2004 %T Secure regression for vertically partitioned, partially overlapping data %A A. F. Karr %A C. N. Kohnen %A X. Lin %A J. P. Reiter %A A. P. Sanil %B ASA Proceedings 2004 %G eng %0 Journal Article %J Int. Journal of Uncertainty, Fuzziness and Knowledge Based Systems %D 2002 %T Software Systems for Tabular Data Releases %A Adrian Dobra %A Alan F. Karr %A Ashish P. Sanil %A Stephen E. Fienberg %B Int. Journal of Uncertainty, Fuzziness and Knowledge Based Systems %V 10 %P 529-544 %G eng %0 Journal Article %J Journal of Forecasting %D 2002 %T Statistical Analyses of Freeway Traffic Flows %A Claudia Tebaldi %A Mike West %A Alan F. Karr %B Journal of Forecasting %V 21 %P 39–68 %G eng %0 Journal Article %J Journal of Transportation and Statistics %D 2002 %T Statistically-Based Validation of Computer Simulation Models in Traffic Operations and Management %A Jerome Sacks %A Nagui M. Rouphail %A B. Brian Park %A Piyushimita Thakuriah %K Advanced traffic management systems %K computer simulation %K CORSIM %K model validation %K transportation policy %XThe process of model validation is crucial for the use of computer simulation models in transportation policy, planning, and operations. This article lays out obstacles and issues involved in performing a validation. We describe a general process that emphasizes five essential ingredients for validation: context, data, uncertainty, feedback, and prediction. We use a test bed to generate specific (and general) questions as well as to give concrete form to answers and to the methods used in providing them. The traffic simulation model CORSIM serves as the test bed; we apply it to assess signal-timing plans on a street network of Chicago. The validation process applied in the test bed demonstrates how well CORSIM can reproduce field conditions, identifies flaws in the model, and shows how well CORSIM predicts performance under new (untried) signal conditions. We find that CORSIM, though imperfect, is effective with some restrictions in evaluating signal plans on urban networks.

%B Journal of Transportation and Statistics %V 5 %G eng %0 Journal Article %J Concrete Science and Engineering %D 2000 %T Statistical studies of the conductivity of concrete using ASTM C1202?94 %A A. F. Karr %A S.S. Jaiswal %A J.D. Picka %A T. Igusa %A S. P. Shah %A B.E. Ankenman %A P. Styer %B Concrete Science and Engineering %V 2 %P 97-105 %G eng %0 Book Section %D 1998 %T SoftStat ?97: Advances in Statistical Software 6 %A A. F. Karr %A G. Eick %A A. Mockus %A T.L. Graves %E W. Badilla %E F. Faulbaum %I Lucius & Lucius %P 3-10 %G eng %& Web-based text visualization %0 Book Section %B Modelling Longitudinal and Spatially Correlated Data %D 1997 %T Scaled Link Functions for Heterogeneous Ordinal Response Data* %A Xie, Minge %A Simpson, Douglas G %A Carroll, Raymond J. %E Gregoire, Timothy G. %E Brillinger, David R. %E Diggle, PeterJ. %E Russek-Cohen, Estelle %E Warren, William G. %E Wolfinger, Russell D. %K Aggregated observations %K Generalized likelihood inference %K Marginal modeling approach %K Ordinal regression %XThis paper describes a class ordinal regression models in which the link function has scale parameters that may be estimated along with the regression parameters. One motivation is to provide a plausible model for group level categorical responses. In this case a natural class of scaled link functions is obtained by treating the group level responses as threshold averages of possible correlated latent individual level variables. We find scaled link functions also arise naturally in other circumstances. Our methodology is illustrated through environmental risk assessment data where (correlated) individual level responses and group level responses are mixed.

%B Modelling Longitudinal and Spatially Correlated Data %S Lecture Notes in Statistics %I Springer New York %V 122 %P 23-36 %@ 978-0-387-98216-8 %G eng %U http://dx.doi.org/10.1007/978-1-4612-0699-6_3 %R 10.1007/978-1-4612-0699-6_3 %0 Journal Article %J Environmental and Ecological Statistics %D 1997 %T Spatial sampling and the environment: some issues and directions %A Dennis D. Cox %A Lawrence H. Cox %A ENSOR, KATHERINE B. %K environmental monitoring %K experimental design %K kriging %K multiphase sampling %K spatial statistics %B Environmental and Ecological Statistics %I Kluwer Academic Publishers %V 4 %P 219-233 %G eng %U http://dx.doi.org/10.1023/A%3A1018578513217 %R 10.1023/A:1018578513217 %0 Journal Article %J Atmospheric Environment %D 1995 %T Shrinking a wet deposition network %A Oehlert, Gary W. %K Monitoring network %K network design %K spatial smoothing %K trend analysis %XSuppose that we must delete stations from a monitoring network. Which stations should be deleted if we wish the remaining network to have the smallest possible trend estimate variances? We use the spatial-temporal model described in Oehlert (1993, J. Am. Statist. Assoc., 88, 390–399), to model concentration of sulfate in wet deposition. Based on this model and three criteria, we choose good sets of candidate stations for deletion from the NADP/NTN network. We use the criteria: that the sum of 11 regional trend estimate variances be as small as possible, that the sum of local trend estimation variance be as small as possible, and that the sum of local mean estimation variance be as small as possible. Good choices of stations for deletion result in a modest increase in criteria (about 7 to 34%) for 100 stations deleted from the network, while random sets of 100 stations can increase criteria by a factor of two or more.

%B Atmospheric Environment %V 30 %P 1347–1357 %G eng %R 10.1016/1352-2310(95)00333-9 %0 Generic %D 1994 %T Statistics and Materials Science: Report of a Workshop %A A. F. Karr %I National Institute of Statistical Sciences %G eng