JSM Preliminary Online Program
This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.


Back to main JSM 2007 Program page

Activity Number: 332
Type: Contributed
Date/Time: Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #310244
Title: Small Sample Conditional Inference for the Cox Model
Author(s): Juan Zhang*+ and John E. Kolassa
Companies: Rutgers University and Rutgers University
Address: Dept of Statistics and Biostatistics, Piscataway, NJ, 08855,
Keywords: Saddlepoint approximation ; Cox model ; Conditional inference ; Modified signed likelihood ratio statistic ; Priors ; Partial differential equation
Abstract:

We apply saddlepoint approximation to conditional inference under the Cox model. With the presence of nuisance parameters, inference about the parameter of interest may be based on the signed root of the likelihood ratio statistic. DiCiccio and Martin (1993) proposed an alternative quantity to the signed root of the likelihood ratio statistic, which involves the Bayesian approach. The prior function of the parameters can be obtained from a partial differential equation. For the Cox model, finding the prior function is not trivial. We provide a way to solve the partial differential equation, apply it to the Cox model, and perform numerical studies in small sample size settings.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2007 program

JSM 2007 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised September, 2007