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Flexible regression models with cubic splines

Statistics in Medicine · 1989 · Vol. 8(5) · pp. 551–561
Sylvain DurrlemanRichard Simon

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.

Statistical Methods and InferenceOptimal Experimental Design MethodsAdvanced Statistical Methods and ModelsCovariateMultivariate adaptive regression splinesRegressionRegression analysisParametric statisticsSimple (philosophy)Computer scienceStatisticsSpline (mechanical)Nonparametric regression

MeSH terms

AdultAge FactorsAgedFemaleHumansLymphoma, Non-HodgkinMaleMiddle AgedPrognosisRegression AnalysisSex FactorsModels, StatisticalHeart Transplantation
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