Publications

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Displaying 1 through 8 of 8 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

Campbell K, Niare S, Herman Kuiper J. A mathematical model of cartilage regeneration after chondrocyte and stem cell implantation – II: the effects of co-implantation. J Tissue Eng. 2019 Mar 15;10:1-14. doi: 10.1177/2041731419827792

Campbell K, Naire S, Herman Kuiper J. A mathematical model of cartilage regeneration after chondrocyte and stem cell implantation – I: the effects of growth factors. J Tissue Eng. 2019 Mar;10:1-16. doi: 10.1177/2041731419827791

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

Davis AE, Mehrotra S, Friedewald J, Ladner D. Characteristics of a simulation model of the national kidney transplantation system. Poster presented at the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World; December 2013. [abstract] Ieee/Acm Trans Comput Biol Bioinform. 2013 Dec; p.2320-9.

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.