Flexible regression models with cubic splines

Flexible regression models with cubic splines We describe the use of cubic splines in regression models to represent the relationship between the response variable and a vector of covariates. This simple method can help prevent the problems that result from inappropriate linearity assumptions. We compare restricted cubic spline regression to non‐parametric procedures for characterizing the relationship between age and survival in the Stanford Heart Transplant data. We also provide an illustrative example in cancer therapeutics. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Statistics in Medicine Wiley

Flexible regression models with cubic splines

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Publisher
Wiley
Copyright
"Copyright © 1989 Wiley Subscription Services, Inc., A Wiley Company"
ISSN
0277-6715
eISSN
1097-0258
D.O.I.
10.1002/sim.4780080504
Publisher site
See Article on Publisher Site

Abstract

We describe the use of cubic splines in regression models to represent the relationship between the response variable and a vector of covariates. This simple method can help prevent the problems that result from inappropriate linearity assumptions. We compare restricted cubic spline regression to non‐parametric procedures for characterizing the relationship between age and survival in the Stanford Heart Transplant data. We also provide an illustrative example in cancer therapeutics.

Journal

Statistics in MedicineWiley

Published: May 1, 1989

Keywords: ; ;

References

  • Statistical methods for the identification and use of prognostic factors
    Armitage, P.; Gehan, E. A.
  • Fitting segmented polynomial regression models whose join points have to be estimated
    Gallant, R.; Fuller, W.
  • National Cancer Institute sponsored study of classification of non‐Hodgkin's lymphomas

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