Publications

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Displaying 1 through 7 of 7 publications.

Conover MM, Rothman KJ, Sturmer T, Ellis AR, Poole C, Jonsson Funk M. Propensity score trimming mitigates bias due to covariate measurement error in inverse probability of treatment weighted analyses: a plasmode simulation. Stat Med. 2021 Apr;40(9):2101-12. doi: 10.1002/sim.8887

Webster-Clark M, Sturmer T, Wang T, Man K, Marinac‐Dabic D, Rothman KJ, Ellis AR, Gokhale M, Lunt M, Girman C, Glynn RJ. Using propensity scores to estimate effects of treatment initiation decisions: state of the science. Stat Med. 2021 Mar 30;40(7):1718-35. doi: 10.1002/sim.8866

Quintana M, Shrader J, Slota C, Joe G, McKew JC, Fitzgerald M, Gahl WA, Berry S, Carrillo N. Bayesian model of disease progression in GNE myopathy. Stat Med. 2019 Apr 15;38(8):1459-74. doi: 10.1002/sim.8050

Neugebauer R, Schmittdiel JA, Zhu Z, Rassen JA, Seeger JD, Schneeweiss S. High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions. Stat Med. 2015 Feb 28;34(5):753-81. doi: 10.1002/sim.6377

Martin SA, Coon CD, McLeod LD, Chandran A, Arnold LM. Evaluation of the fibromyalgia diagnostic screen in clinical practice. J Eval Clin Pract. 2014 Apr;20(2):158-65. doi: 10.1111/jep.12102

Brown TM, Garg S, Chandran AB, McNett M, Silverman SL, Hadker N. The impact of 'best-practice' patient care in fibromyalgia on practice economics. J Eval Clin Pract. 2012 Aug 1;18(4):793-8.

Garcia R, Benet M, Arnau C, Cobo E. Efficiency of the cross-over design: an empirical estimation. Stat Med. 2004 Dec 30;23(24):3773-80. doi: 10.1002/sim.2072.