The Reliability of Penalized Models in Survival Analysis for Sperm Count Data: Using the Value First Deritative Parametrization in the Penalized Likelihood Framework

• Activity Number: 88
• Type: Contributed
• Date/Time: Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Ronny Westerman*+
• Companies: University of Marburg
• Keywords: Penalized Models ; Value First Derivative Paramemtrization ; Double Penalty ; Survival Analysis ; Sperm count data

Abstract

In Survival analysis the parametric assumption seems to be too restrictive for many practical applications. Nonparametric techniques will be often seen as an alternative to overcome such problems in limitations. The motivation using penalized splines (P-splines) yields on the compromise between smoothing and regression splines. One problem involving penalized splines is considered with use of single penalties. In this paper one want to apply the value-first derivative parametrization (VFDP) introduced by Costa et al. 2008 for sperm count data. The convenience of VFDP takes account for the right parametrization in the penalties and the optional use for double penalties. The appropriated dataset enfold more than 2.000 sperm count records from the department of andrology at Marburg University Hospital Germany were sampled between 1949 and 1998. For analysing the statistical association between male sperm count and survival one conduct the Mortality-follow-up until December 31th 2006.The main purpose of this paper is aimed on the comparison of the performance for certain penality parametrization (single or double) as nonparametric fashion in proportional hazard context.