articleTop 10% cited
Flexible regression models with cubic splines
Statistics in Medicine · 1989 · Vol. 8(5) · pp. 551–561
Sylvain Durrleman✉(Zimmer Biomet (Netherlands))Richard Simon(Office of the Director)
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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References
Some Aspects of the Spline Smoothing Approach to Non-Parametric Regression Curve Fitting
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1985 · 1,123 citations
National cancer institute sponsored study of classifications of non-hodgkin's lymphomas. Summary and description of a working formulation for clinical usage
Cancer · 1982 · 3,079 citations
Applied Regression Analysis
Technometrics · 1982 · 5,826 citations
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