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A strategy for modelling the effect of a continuous covariate in medicine and epidemiology.
Royston P. Royston P. Stat Med. 2000 Jul 30;19(14):1831-47. doi: 10.1002/1097-0258(20000730)19:14<1831::aid-sim502>3.0.co;2-1. Stat Med. 2000. PMID: 10867674
Royston and Altman's recent work on fractional polynomials has extended the range of available functions. It is clearly crucial that the chosen final model fits the data well. ...
Royston and Altman's recent work on fractional polynomials has extended the range of available functions. It is clearly crucial that
Visualizing and assessing discrimination in the logistic regression model.
Royston P, Altman DG. Royston P, et al. Stat Med. 2010 Oct 30;29(24):2508-20. doi: 10.1002/sim.3994. Stat Med. 2010. PMID: 20641144
Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study.
Marshall A, Altman DG, Royston P, Holder RL. Marshall A, et al. Among authors: royston p. BMC Med Res Methodol. 2010 Jan 19;10:7. doi: 10.1186/1471-2288-10-7. BMC Med Res Methodol. 2010. PMID: 20085642 Free PMC article.
Modelling continuous exposures with a 'spike' at zero: a new procedure based on fractional polynomials.
Royston P, Sauerbrei W, Becher H. Royston P, et al. Stat Med. 2010 May 20;29(11):1219-27. doi: 10.1002/sim.3864. Stat Med. 2010. PMID: 20191601
Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response.
Binder H, Sauerbrei W, Royston P. Binder H, et al. Among authors: royston p. Stat Med. 2013 Jun 15;32(13):2262-77. doi: 10.1002/sim.5639. Epub 2012 Oct 3. Stat Med. 2013. PMID: 23034770
Selection of important variables and determination of functional form for continuous predictors in multivariable model building.
Sauerbrei W, Royston P, Binder H. Sauerbrei W, et al. Among authors: royston p. Stat Med. 2007 Dec 30;26(30):5512-28. doi: 10.1002/sim.3148. Stat Med. 2007. PMID: 18058845
Assuming linear functions, stepwise selection and all-subset strategies are discussed; the key tuning parameters are the nominal P-value for testing a variable for inclusion and the penalty for model complexity, respectively. ...
Assuming linear functions, stepwise selection and all-subset strategies are discussed; the key tuning parameters are the nominal P-va …
Modelling to extract more information from clinical trials data: On some roles for the bootstrap.
Sauerbrei W, Royston P. Sauerbrei W, et al. Among authors: royston p. Stat Med. 2007 Nov 30;26(27):4989-5001. doi: 10.1002/sim.2954. Stat Med. 2007. PMID: 17607706
Interaction of treatment with a continuous variable: simulation study of significance level for several methods of analysis.
Royston P, Sauerbrei W. Royston P, et al. Stat Med. 2013 Sep 30;32(22):3788-803. doi: 10.1002/sim.5813. Epub 2013 Apr 12. Stat Med. 2013. PMID: 23580422
A new strategy for meta-analysis of continuous covariates in observational studies.
Sauerbrei W, Royston P. Sauerbrei W, et al. Among authors: royston p. Stat Med. 2011 Dec 10;30(28):3341-60. doi: 10.1002/sim.4333. Epub 2011 Sep 22. Stat Med. 2011. PMID: 21953493
Comments on design and monitoring of survival trials in complex scenarios.
Barthel FM, Babiker A, Royston P, Parmar MK. Barthel FM, et al. Among authors: royston p. Stat Med. 2019 Jun 30;38(14):2704. doi: 10.1002/sim.8087. Stat Med. 2019. PMID: 31168886 No abstract available.
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