M.J. van der Laan, S. Rose (2018). Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies. New York, Springer.
M.J. van der Laan, S. Rose (2011). Targeted Learning: Causal Inference for Observational and Experimental Data. New York, Springer.
*Trainee author +Senior author
S. Rose, S.L. Normand. Robust estimation for multiple unordered treatments: Evaluating drug-eluting coronary artery stents, second revise & resubmit.
C. Carroll*, M. Chernew, A.M. Fendrick, J. Thompson, S. Rose+. Effects of episode-based payment on health care spending and utilization: Evidence from perinatal care in Arkansas, revise & resubmit. [NBER Working Paper #23926]
G. Ezaz, D. Leffler, S. Beach, R. Schoen, S. Crockett, R. Gourevitch, S. Rose, M. Morris, D. Carrell, J. Greer, A. Mehrotra. Do personality differences explain variation in physician adenoma detection rates? revise & resubmit.
L. Gilstrap, A. Mehrotra, B. Bai, S. Rose, R. Blair, M. Chernew. National rates of initiation and intensification of diabetic therapy among patients with commercial insurance, revise & resubmit.
M. Barnett, Z. Song, A. Bitton, S. Rose, B. Landon. Gatekeeping and patterns of outpatient care in the post-health reform era, revise & resubmit.
S. Rose, T. McGuire. Statistical fit and algorithmic fairness in risk adjustment for health policy, under review. [arXiv:1803.05513]
A. McDowell*, A. Progovac, B.L. Cook, S. Rose+. Estimating the population characteristics and health status of privately insured gender minorities, under review.
S. Bergquist*, T. McGuire, T. Layton, S. Rose+. Medicare risk adjustment with systematically missing data, under review.
G. Brooks, S. Bergquist, M.B. Landrum, S. Rose+, N. Keating+. Classifying lung cancer stage from health care claims: Comparison of a clinical algorithm and a machine learning approach, under review.
M. Nakamura, S. Toomey, A. Zaslavsky, C. Petty, C. Lin, G. Savova, S. Rose, M. Brittan, J. Lin, M. Bryant, S. Ashrafzadeh, M. Schuster. Impact of clinical data on adjustment of pediatric readmission rates, under review.
S. Crockett, R. Gourevitch, M. Morris, D. Carrell, S. Rose, J. Greer, R. Schoen, A. Mehrotra (2018). Endoscopist factors that influence serrated polyp detection: A multi-center study. Endoscopy, in press.
S. Rose (2018). Robust machine learning variable importance analyses of medical conditions for health care spending. Health Services Research. Advance online publication. doi:10.1111/1475-6773.12848. [PDF]
R. Gourevitch, S. Rose, S. Crockett, M. Morris, D. Carrell, J. Greer, R. Pai, R. Schoen, A. Mehrotra (2018). Variation in pathologist classification of colorectal adenomas and serrated polyps. American Journal of Gastroenterology, 113:431-39. [PDF]
C. Lee, S. Haneuse, H.L. Wang, S. Rose, S. Spellman, M. Verneris, K. Hsu, K. Fleischhauer, S. Lee, R. Abdi (2018). Prediction of acute graft-versus-host disease following hematopoietic cell transplantation. PLoS One, 13(1):e0190610. [Link]
F. Mateen, E. McKenzie, S. Rose+ (2018). Medical schools in fragile states: Implications for delivery of care. Health Services Research. Advance online publication. doi:10.1111/1475-6773.12709. [PDF]
Editorial in HSR by Snowden & Muoto
A.J. Rosellini*, F. Dussaillant, J. Zubizarreta, R. Kessler, S. Rose+ (2018). Predicting posttraumatic stress disorder following a natural disaster. Journal of Psychiatric Research, 96:15-22. [Link]
Press coverage in Psychology Today
A. Mehrotra, M. Morris, R. Gourevitch, D. Carrell, D. Leffler, S. Rose, J. Greer, S. Crockett, A. Baer, R. Schoen (2018). Physician characteristics associated with higher adenoma detection rate. Gastrointestinal Endoscopy, 87(3):778-86. [Link]
S. Bergquist*, G. Brooks, N. Keating, M.B. Landrum, S. Rose+ (2017). Classifying lung cancer severity with ensemble machine learning in health care claims data. Proceedings of Machine Learning Research, 68:25-38. [PDF]
Project Website: CancerCLAS.org
Video summary: Talks@12: Data Science & Medicine (21:38-28:52)
A. Sinaiko, T. Layton, S. Rose, T. McGuire (2017). Implications of family risk pooling for individual health insurance markets. Health Services and Outcomes Research Methodology, 17(3):219-36. [Link]
A. Shrestha*, S. Bergquist*, E. Montz, S. Rose+ (2017). Mental health risk adjustment with clinical categories and machine learning. Health Services Research. Advance online publication. doi:10.1111/1475-6773.12818. [PDF]
M. Barnett, Z. Song, S. Rose, A. Bitton, M. Chernew, B. Landon (2017). Insurance transitions and changes in physician and emergency department utilization: An observational study. Journal of General Internal Medicine. 32(10):1146-55. [Link]
Editorial in JGIM by Dworsky
S. Rose, S. Bergquist*, T. Layton (2017). Computational health economics for identification of unprofitable health care enrollees. Biostatistics, 18(4):682-94. [Link][Code]
Harvard Medical School News: "Deep Dive"
Video summary: Computational Health Economics
D. Carrell, R. Schoen, D. Leffler, M. Morris, S. Rose, A. Baer, S. Crockett, R. Gourevitch, K. Dean, A. Mehrotra (2017). Challenges in adapting existing clinical natural language processing systems to multiple, diverse healthcare settings. Journal of the American Medical Informatics Association, 24(5):986-91. [Link]
A. Mehrotra, H. Huskamp, J. Souza, L. Uscher-Pines, S. Rose, B. Landon, A. Jena, A. Busch (2017). Rapid growth in mental health telemedicine use among Medicare beneficiaries, wide variation across states. Health Affairs, 36(5):909-17. [Link]
Harvard Medical School News: "Mental Health on the Line"
Press coverage in Politico
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, AJMC
M. Schuler*, S. Rose+ (2017). Targeted maximum likelihood estimation for causal inference in observational studies. American Journal of Epidemiology, 185(1):65-73. [Link]
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]
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):1022-8. [PDF]
Harvard Medical School News: "Managing the Marketplace"
Press briefing video: Behavioral Health, National Press Club (0:04:21-0:11:33)
Press coverage in AJMC
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):440-8. [Link]
Featured in official letter to CMS signed by 22 health organizations, AMGA letter
Discussed by Health Affairs Blog, 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
Evaluated by Faculty of 1000
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):668-75. [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. [PDF]
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, Los Angeles Times
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): 1704-14. [Link]
Harvard Medical School News: "Four Years In..." and "Health Reform Progress"
Press coverage in The New York Times, US News, The Boston Globe, AJMC, Modern Healthcare
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):3289-302. [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):765-77. [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):792–6. [PDF]
Featured in issue editorial
S. Rose, J. Snowden, K. Mortimer (2011). Rose et al. respond to “G-computation and standardization in epidemiology.” Am J Epidemiol, 173(7):743–4. [PDF]
J. Snowden, S. Rose, K. Mortimer (2011). Implementation of G-Computation on a simulated data set: demonstration of a causal inference technique. Am J Epidemiol, 173(7):731–8. [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]
R. Ellis, B. Martins, S. Rose (2017). Risk adjustment for health plan payment. In T. McGuire, R. van Kleef, eds. Risk Adjustment, Risk Sharing and Premium Regulation in Health Insurance Markets: Theory and Practice. Elsevier. [Working Paper Version]
L. Kunz, S. Rose, D. Spiegelman, S.L. Normand (2017). An overview of approaches for comparative effectiveness research. In C. Gatsonis, S. Morton, eds. Methods in Comparative Effectiveness Research. Boca Raton: Chapman and Hall/CRC.
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.
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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