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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.
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Sylvain Durrleman
Richard Simon
Statistics in Medicine
Center for Cancer Research
Office of the Director
Zimmer Biomet (Netherlands)
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Durrleman et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69d56ebf75589c71d767d5b7 — DOI: https://doi.org/10.1002/sim.4780080504
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