JSM 2004 - Toronto

Abstract #300098

This is the preliminary program for the 2004 Joint Statistical Meetings in Toronto, Canada. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2004); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

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 2004 Program page
Activity Number: 207
Type: Invited
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #300098
Title: Outcome Dependent Sampling, Biased Sampling, and Truncated Sampling: Connections and Applications in Epidemiologic Studies
Author(s): Jing Qin*+
Companies: Memorial Sloan-Kettering Cancer Center
Address: Dept. of Epidemiology and Biostatistics, New York, NY, 10021,
Keywords: outcome-dependent sampling ; biased sampling ; truncated sampling
Abstract:

Outcome dependent sampling is a sampling strategy that implies that the probability of being sampled depends directly on the value of the outcome variable or dependent vairable. It is a cost-effective way to enhance the efficiency in epidemiologic studies. Biased sampling is a convenient or economic sampling technique in the collection of positive-valued or lifetime data. Biased sampling occurs when healthier patients are more likely to participate a study. In survival analysis, failure time data sometimes are ascertained retrospectively subject to a certain criterion. Truncation sampling occurs when only those who have experienced the terminating event are qualified to be recruited.

In this talk we will point out the connection between those sampling schemes and likelihood decompositions. Different approaches are discussed, including conditional inference, pseudo-likelihood based inference and empirical likelihood method.

  • 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 2004 program

JSM 2004 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 March 2004