JSM 2005 - Toronto

Abstract #303913

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. 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, 2005); 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.


The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Add ALL Displayed Sessions To My Program  /  View My Program  /  View My Program (condensed)  /  What is My Program?


Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 190
Type: Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #303913
Title: Parameter Estimation in the Presence of Coarsened Data
Author(s): Sergey S. Tarima*+ and Richard Kryscio and Yuriy Dmitriev
Companies: University of Kentucky and University of Kentucky and Tomsk State University
Address: 1608 University CT Apt E107, Lexington, KY, 40503, United States
Keywords: missing data ; coarsened data ; parameter estimation
Abstract:

A random sample in the presence of coarsened observations is used for estimating a vector of population parameters. A method proposed in this paper combines sample estimates obtained from different subsamples of an original sample and produces a vector of estimators accumulating the information from all sample estimates. This estimator is asymptotically efficient and can be effectively applied to nonignorable coarsening. The estimation based on this approach was applied to an artificial example and a real dataset. The results are provided.


  • 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 2005 program

JSM 2005 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 2005