Abstract
An estimate of a survival curve S(x) for censored data is given by the non-parametric Kaplan-Meier method, which provides an estimate of the empirical survival curve and estimators of the standard errors. We use the software package Confit, developed by WTI, which is designed to produce a smoothed approximating spline, subject to imposed constraints on the function or its derivatives over an interval. The algorithm solves a constrained least-squares problem parameterized by an appropriate spline subspace (using a B-spline representation) . The constraints impose some additional constraints on these coefficients that are converted into a quadratic programming problem. We will discuss the algorithm used to solve the quadratic programming problem, and give applications to illustrate our method on several data sets.
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© 1998 Springer-Verlag Berlin Heidelberg
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Ramirez, D.E., Smith, P.W. (1998). Applications of Smoothed Monotone Regression Splines and Smoothed Bootstrapping in Survival Analysis. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_59
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DOI: https://doi.org/10.1007/978-3-662-01131-7_59
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
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