SCI brings nearly thirty years of experience and deep expertise. We are proud to have that reflected through industry recognition. The following list shows some of the awards our staff has received.
Our work within the drug development and clinical trial communities represents our staff’s commitment to becoming recognized experts in numerous fields. SCI is well-known by our high-quality work and industry contributions. See below for selected committee and panel participation.
We believe in the importance of sharing knowledge and helping to train the next generation of statisticians. See below for selected teaching and mentoring activities.
In addition to publishing original research, our staff has served on editorial boards for the following peer reviewed publications.
SCI is integrally involved in writing on statistical methodology and trials on which we have worked. Below, please find a collection of selected publications listed in reverse chronological order. To view a complete list of published articles, abstracts, and books, please contact us.
Buhr KA, Downs M, Rhorer J, Bechhofer R, Wittes J. Reports to independent data monitoring committees: An appeal for clarity, completeness, and comprehensibility. Therapeutic Innovation and Regulatory Science 2018; 52:459-468.
Russell S, Bennett J, Wellman JA, Chung DC, Yu ZF, Tillman A, Wittes J, Pappas J, Elci O, McCague S, Cross D, Marshall KA, Walshire J, Kehoe TL, Reichert H, Davis M, Raffini L, George LA, Hudson FP, Dingfield L, Zhu X, Haller JA, Sohn EH, Mahajan VB, Pfeifer W, Weckmann M, Johnson C, Gewaily D, Drack A, Stone E, Wachtel K, Simonelli F, Leroy BP, Wright JF, High KA, Maguire AM. Efficacy and safety of voretigene neparvovec (AAV2-hRPE65v2) in patients with RPE65-mediated inherited retinal dystrophy: A randomised, controlled, open-label, phase 3 trial. Lancet 2017; 390:849-860.
Yusuf S, Wittes J. Interpreting geographic variations in results of randomized, controlled trials. N Engl J Med 2016; 375:2263-2271.
Gregg NM, Kim AE, Gurol ME, Lopez OL, Aizenstein HJ, Price JC, Mathis CA, James JA, Snitz BE, Cohen AD, Kamboh MI, Minhas D, Weissfeld LA, Tamburo EL, Klunk WE. Incidental cerebral microbleeds and cerebral blood flow in elderly individuals. JAMA Neurol 2015; 72:1021-1028.
Wittes J, Crowe B, Chuang-Stein C, Guettner A, Hall D, Odenheimer D, Xi HA, Kramer J. The FDA’s final rule on expedited safety reporting: Statistical considerations. Stat Biopharm Res 2015; 7:174-190.
Shen Y, Anderson AB, Sinha R, Li Y. Joint modeling tumor burden and time to event data in oncology trials. Pharmaceutical Statistics 2014, 13:286-293.
Walters KA, Huang Y, Azaro M, Tobin K, Lehner T, Brzustowicz LM, Vieland VJ. Meta-analysis of repository data: impact of data regularization on NIMH schizophrenia linkage results. PLoS One 2014; 9:e84696.
Snitz BE, Weissfeld LA, Lopez OL, Kuller LH, Saxton J, Singhabahu DM, Klunk WE, Mathis CA, Price JC, Ives DG, Cohen AD, McDade E, Dekosky ST. Cognitive trajectories associated with beta-amyloid deposition in the oldest-old without dementia. Neurology 2013; 80:1378-1384.
Rosario BL, Weissfeld LA, Laymon CM, Mathis CA, Klunk WE, Berginc MD, James JA, Hoge JA, Price JC. Inter-rater reliability of manual and automated region-of-interest delineation for PiB PET. Neuroimage 2011; 55:933-941.
Sattar A, Weissfeld LA, Molenberghs G. Analysis of non-ignorable missing and left-censored longitudinal data using a weighted random effects tobit model. Stat Med 2011; 30:3167-3180.
Walters KA, Li Y, Tiwari RC, Zou Z. A weighted-least-squares estimation approach to comparing trends in age-adjusted cancer rates across overlapping regions. J Data Sci 2011; 8:631-644.
Averbuch SD, Anderson AB, Boerner SA, LoRusso PM. Making the investigational oncology pipeline more efficient and effective: Are we headed in the right direction? Cancer Clinical Research 2010, 16:5956-5962.
Downs M, Tucker K, Christ-Schmidt H, Wittes J. Some practical problems in implementing randomization. Clin Trials 2010; 7:235-245.
Rhorer J, Ambrose C, Dickinson S, Hamilton H, Oleka N, Malinoski F, Wittes J. Efficacy of live attenuated influenza vaccine in children: a meta-analysis of nine randomized clinical trials. Vaccine 2009; 27:1101-1110.
Huang DT, Weissfeld LA, Kellum JA, Yealy DM, Kong L, Martino M, Angus DC. Risk prediction with procalcitonin and clinical rules in community-acquired pneumonia. Ann Emerg Med 2008; 52:48-58 e42.
Yu ZF, Catalano PJ. A simulation study of quantitative risk assessment for bivariate continuous outcomes. Risk Anal 2008; 28:1415-1430.
Wittes J, Barrett-Connor E, Braunwald E, Chesney M, Cohen HJ, Demets D, Dunn L, Dwyer J, Heaney RP, Vogel V, Walters L, Yusuf S. Monitoring the randomized trials of the Women’s Health Initiative: The experience of the Data and Safety Monitoring Board. Clin Trials 2007; 4:218-234.
Proschan M, Lan K, Wittes J. Statistical Monitoring of Clinical Trials: A Unified Approach. New York: Springer, 2006.
Weissfeld LA. Multiple Endpoints in Clinical Trials. Encyclopedia of Biostatistics. John Wiley & Sons, Ltd, 2005.
Yu Z, Catalano P, Quantitative risk assessment for multivariate continuous outcomes with application to neurotoxicology: the bivariate case. Biometrics 2005; 61:757‑766.
Christ-Schmidt H, Downs M. A SAS Macro to generate enhanced Kaplan‑Meier plots. Proceedings of the Thirtieth Annual Conference of the SAS Users Group International Conference 2004.
Anderson A, Prentice R. On the accommodation of disease rate correlations in aggregate data studies of disease risk factors. Biometrics 1998, 54:1527-1540.
Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, Coley CM, Marrie TJ, Kapoor WN. A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med 1997; 336:243-250.
Lan K, Wittes J. The B-value: A tool for monitoring data. Biometrics 1988; 44:579-585.
Yusuf S, Wittes J, Probstfield J, Tyroler H. Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials. JAMA 1991; 266:93-98.
Wei LJ, Lin DY, Weissfeld LA. Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. J Am Statist Assoc 1989; 84:1065-1073.
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