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Flexible regression models with cubic splines
Author(s) -
Durrleman Sylvain,
Simon Richard
Publication year - 1989
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780080504
Subject(s) - covariate , multivariate adaptive regression splines , regression , regression analysis , parametric statistics , simple (philosophy) , computer science , statistics , spline (mechanical) , nonparametric regression , mathematics , smoothing spline , econometrics , spline interpolation , philosophy , structural engineering , epistemology , engineering , bilinear interpolation
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.