Cubic splines to model relationships between continuous variables and outcomes: a guide for clinicians-Reference-Cited by-同舟云学术

Cubic splines to model relationships between continuous variables and outcomes: a guide for clinicians

Published:2019-10-01 Issue:4 Volume:55 Page:675-680
ISSN:0268-3369
Container-title:Bone Marrow Transplantation
language:en
Short-container-title:Bone Marrow Transplant

Author:

Gauthier J.,Wu Q. V.,Gooley T. A.

Publisher

Springer Science and Business Media LLC

Subject

Transplantation,Hematology

Link

http://www.nature.com/articles/s41409-019-0679-x.pdf

Reference8 articles.

1. Box GEP. Robustness in Statistics. Academic Press; 1979. p. 201–36. https://doi.org/10.1016/b978-0-12-438150-6.50018-2

2. Stone CGKCY. Additive splines in statistics. In: Proceedings of the American Statistical Association; 1985. p. 45–8.

3. Devlin TF. Spline functions for logistic regression modelling. In: Proceedings of the 11th Annual SAS Users Group International Conference; 1986. p. 646–51.

4. Harrell JFE. Regression modeling strategies. Springer; 2015. https://doi.org/10.1007/978-3-319-19425-7 .

5. Heinzl H, Kaider A. Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions. Comput Methods Prog Biomed. 1997;54:201–8. https://doi.org/10.1016/s0169-2607(97)00043-6.

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