*Trainee author +Senior author
S. Rose, S. Bergquist*, T. Layton. Computational health economics for identification of vulnerable unprofitable health care enrollees, revise & resubmit.
A.J. Rosellini*, F. Dussaillant, J. Zubizarreta, R. Kessler, S. Rose+. Machine learning methods for predicting posttraumatic stress disorder following a natural disaster, revise & resubmit.
A. Mehrotra, H. Huskamp, J. Souza, L. Uscher-Pines, S. Rose, B. Landon, A. Jena, A. Busch. Use of telemental health among rural Medicare beneficiaries with mental illness, revise & resubmit.
D. Carrell, R. Schoen, D. Leffler, M. Morris, S. Rose, A. Baer, S. Crockett, R. Gourevitch, K. Dean, A. Mehrotra. Adapting a natural language processing system for measuring colonoscopy quality to multiple, diverse healthcare settings, revise & resubmit.
S. Rose. Robust machine learning for variable importance in health spending, under review.
A. Sinaiko, T. Layton, S. Rose, T. McGuire. Family risk pooling in individual health insurance markets, under review.
M. Barnett, Z. Song, S. Rose, A. Bitton, M. Chernew, B. Landon. The contribution of insurance transitions to care fragmentation, under review.
S. Rose, S.L. Normand. Robust estimation for multiple unordered treatments: Evaluating drug-eluting coronary artery stents, under review.
A. Shrestha*, S. Bergquist*, E. Montz, S. Rose+. Mental health risk adjustment with clinical categories and machine learning, under review.
F. Mateen, E. McKenzie, S. Rose+ (2017). Medical schools in fragile states: Implications for delivery of care. Health Services Research, provisionally accepted.
Z. Song, S. Rose, M. Chernew, D. Gelb Safran (2017). Lower versus higher income populations in the Alternative Quality Contract: Improved quality and similar spending. Health Affairs, 36(1):74-82. [Link]
Harvard Medical School News: "Raising Quality"
Press coverage in The Boston Globe, WBUR
M. Schuler*, S. Rose+ (2017). Targeted maximum likelihood estimation for causal inference in observational studies. American Journal of Epidemiology, 185(1):65-73. [PDF]
J. Spertus, S.L. Normand, R. Wolf, M. Cioffi, A. Lovett, S. Rose+ (2016). Assessing hospital performance after percutaneous coronary intervention using big data. Circulation: Cardiovascular Quality and Outcomes, 9:659-69. [PDF]
S. Rose (2016). A machine learning framework for plan payment risk adjustment. Health Services Research, 51(6):2358-74 . [Link]
E. Montz, T. Layton, A. Busch, R. Ellis, S. Rose, T. McGuire (2016). Risk adjustment simulation: Plans may have incentives to distort mental health and substance use coverage. Health Affairs, 35(6):1022-28. [PDF]
Harvard Medical School News: "Managing the Marketplace"
Press briefing video: Behavioral Health, National Press Club (0:04:21-0:11:33)
S. Rose, A. Zaslavsky, J.M. McWilliams (2016). Variation in accountable care organization spending and sensitivity to risk adjustment: Implications for benchmarking. Health Affairs, 35(3):440-48. [Link]
Featured in official letter to CMS signed by 22 health organizations, AMGA letter
Discussed by HealthExec, CHSR, The Source
A. Mirelman*, S. Rose, J. Khan, S. Ahmed, D. Peters, L. Niessen, A. Trujillo (2016). The relationship between noncommunicable disease occurrence and poverty: Evidence from demographic surveillance in Matlab, Bangladesh. Health Policy and Planning, 31(6):785-92. [PDF]
S. Rose (2015). Targeted learning for pre-analysis plans in public health and health policy research. Observational Studies, 1:294-306. [PDF]
H. Abdul-Baki, R. Schoen, K. Dean, S. Rose, D. Leffler, E. Kuganeswaran, M. Morris, D. Carrell, A. Mehrotra (2015). Public Reporting of Colonoscopy Quality is Associated with an Increase in Endoscopist Adenoma Detection Rate. Gastrointestinal Endoscopy, 82(4):676-82. [Link]
"Editor's Choice" article
Editorial in GIE by Lieberman & Mascarenhas
F. Marcondes, K. Dean, R. Schoen, D. Leffler, S. Rose, M. Morris, A. Mehrotra (2015). The Impact of Exclusion Criteria on a Physician’s Adenoma Detection Rate. Gastrointestinal Endoscopy, 82(4):668-675. [Link]
Video Interview with GIE
Editorial in GIE by Lieberman & Mascarenhas
S. Rose, J. Shi, T. McGuire, S.L. Normand (2015). Matching and imputation methods for risk adjustment in the Health Insurance Marketplaces. Statistics in Biosciences. Advance online publication. doi:10.1007/s12561-015-9135-7. [Link]
R. Kessler, C. Warner, C. Ivany, M. Petukhova, S. Rose, E. Bromet, M. Brown, T. Cai, L. Colpe, K. Cox, C. Fullerton, S. Gilman, M. Gruber, S. Heeringa, L. Lewandowski-Romps, J. Li, A. Millikan-Bell, J. Naifeh, M. Nock, A. Rosellini, N. Sampson, M. Schoenbaum, M. Stein, S. Wessely, A. Zaslavsky, R. Ursano (2015). Predicting suicides after psychiatric hospitalization in US Army soldiers. JAMA Psychiatry, 72(1):49-57. [Link]
Harvard Medical School News
Press coverage in The New York Times, USA Today, US News
A. Street, S. Gilman, A. Rosellini, M. Stein, E. Bromet, K. Cox, L. Colpe, C. Fullerton, M. Gruber, S. Heeringa, L. Lewandowski-Romps, R. Little, J. Naifeh, M. Nock, N. Sampson, M. Schoenbaum, R. Ursano, A. Zaslavsky, R. Kessler, Army STARRS Collaborators (2015). Understanding the elevated suicide risk of female soldiers during deployments. Psychol Med, 45(4):717-26. [Link]
Z. Song, S. Rose, D. Safran, B. Landon, M. Day, M. Chernew (2014). Changes in health care spending and quality 4 years into global payment. N Engl J Med, 371(18): 1704-1714. [Link]
Harvard Medical School News: "Four Years In..." and "Health Reform Progress"
Press coverage in US News, The Boston Globe, AJMC, Modern Healthcare, Medscape
Editorial in NEJM by L.P. Casalino
R. Kessler, S. Rose, K. Koenen, E. Karam, P. Stang, D. Stein, S. Heeringa, E. Hill, I. Liberzon, K. McLaughlin, S. McLean, B. Pennell, M. Petukhova, A. Rossellini, A. Ruscio, V. Shahly, A. Shalev, D. Silove, M. van Ommeren, A. Zaslavsky, M. Angermeyer, E. Bromet, J. Caldas de Almedia, G. de Girolamo, P. de Jonge, K. Demyttenaere, S. Forescu, O. Gureje, J. Haro, H. Hinkov, N. Kawakami, V. Kovess-Masfety, S. Lee, M. Medina-Mora, S. Murphy, F. Navarro-Mateu, M. Piazza, J. Posada-Villa, K. Scott, Y. Torres, M. Viana (2014). How well can post-trauamtic stress disorder be predicted from pre-trauma risk factors? An exploratory study in the WHO World Mental Health Surveys. World Psychiatry, 13(3): 265-74. [PDF]
S. Rose, M.J. van der Laan (2014). Rose and van der Laan respond to "Some advantages of RERI." Am J Epidemiol, 179(6)672-3. [PDF]
S. Rose, M.J. van der Laan (2014). A double robust approach to causal effects in case-control studies. Am J Epidemiol, 179(6):663-9. [PDF]
L. Lewandowski-Romps, C. Peterson, P. Berglund, S. Collins, K. Cox, K. Hauret, B. Jones, R. Kessler, C. Mitchell, N. Park, M. Schoenbaum, M. Stein, R. Ursano, S. Heeringa, Army STARRS Collaborators (2014). Risk factors for accident death in the U.S. Army, 2004-2009. Am J Prev Med, 47(6):745-53. [Link]
K. Wardnaar, H. van Loo, T. Cai, M. Fava, M. Gruber, J. Li, P. de Jonge, A. Nierenberg, M. Petukhova, S. Rose, N. Sampson, R. Schoevers, M. Wilcox, J. Alonso, E. Bromet, M. Bunting, S. Florescu, A. Fukao, O. Gureje, C. Hu, Y. Huang, A. Karam, D. Levinson, M. Medina Mora, J. Posada-Villa, K. Scott, N. Taib, M. Viana, M. Xavier, Z. Zarkov, R. Kessler (2014). The effects of comorbidity in defining major depression subtypes associated with long-term course and severity. Psychological Medicine, 44(15):3289-3302. [Link]
H. van Loo, T. Cai, M. Gruber, J. Li, P. de Jonge, M. Petukhova, S. Rose, N. Sampson, R. Schoevers, K. Wardenaar, M. Wilcox, A. Al-Hamzawi, L. Andrade, E. Bromet, B. Bunting, J. Fayyad, S. Florescu, O. Gureje, C. Hu, Y. Huang, D. Levinson, M. Medina-More, Y. Nakane, J. Posada-Villa, K. Scott, M. Xavier, Z. Zarkov, R. Kessler (2014). Major depressive disorder subtypes to predict long-term course. Depression and Anxiety, 31(9):765-777. [Link]
H. Wang, S. Rose, M.J. van der Laan (2011). Finding quantitative trait loci genes with collaborative targeted maximum likelihood learning. Stat Probabil Lett, 81(7):792–796. [PDF]
Featured in issue editorial
S. Rose, J. Snowden, K.M. Mortimer (2011). Rose et al. respond to “G-computation and standardization in epidemiology.” Am J Epidemiol, 173(7):743–744. [PDF]
J. Snowden, S. Rose, K.M. Mortimer (2011). Implementation of G-Computation on a simulated data set: demonstration of a causal inference technique. Am J Epidemiol, 173(7):731–738. [PDF]
Evaluated by Faculty of 1000
S. Rose, M.J. van der Laan (2011). A targeted maximum likelihood estimator for two-stage designs. Int J Biostat, 7(1):17. [PDF]
ASA Statistics in Epidemiology Graduate Student Travel Award
H. Li, H. Grigoryan, W. Funk, S. Lu, S. Rose, E.R. Williams, S.M. Rappaport (2011). Profiling Cys34 adducts of human serum albumin by fixed-step selected reaction monitoring. Mol Cell Proteomics, 10(3):M110.004606. [PDF]
K. Huen, L. Barcellos, K. Beckman, S. Rose, B. Eskenazi, N. Holland (2011). Effects of PON polymorphisms and haplotypes on molecular phenotype in Mexican-American mothers and children. Environ Mol Mutag, 52(2):105-16. [PDF]
"Editor's Choice" article; featured on issue cover
S. Rose, M. J. van der Laan (2009). Why match? Investigating matched case-control study designs with causal effect estimation. Int J Biostat, 5(1):1. [PDF]
S. Rose, M.J. van der Laan (2008). Simple optimal weighting of cases and controls in case-control studies. Int J Biostat, 4(1):19. [PDF]
S. Cokus, S. Rose, D. Haynor, N. Gronbech-Jensen, M. Pellegrini (2006). Modeling the network of cell cycle transcription factors in the yeast Saccharomyces cerevisiae. BMC Bioinformatics, 7:381. [PDF]
S. Rose (2016). Targeted learning for variable importance. In P. Bühlmann, M. Kane, P. Drineas, M. van der Laan, eds. Handbook of Big Data. Boca Raton: Chapman and Hall/CRC.
L. Kunz, S. Rose, D. Spiegelman, S.L. Normand (2016). An overview of approaches to causal inference. In C. Gatsonis, S. Morton, eds. Methods in Comparative Effectiveness Research. Boca Raton: Chapman and Hall/CRC. [A version of this chapter also appears in L. Kunz's dissertation]
C. Rudin, D. Dunson, R. Irizarry, H. Ji, E. Laber, J. Leek, T. McCormick, S. Rose, C. Schafer, M. van der Laan, L. Wasserman, L. Xue; A Working Group of the American Statistical Association (2014). Discovery with Data: Leveraging Statistics and Computer Science to Transform Science and Society. [PDF]
Amstat News Article
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