JSM 2004 - Toronto

Abstract #301920

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: 275
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #301920
Title: A Generalized Maximum Entropy Approach to Estimating Missing Categorical Dependent Variable Values
Author(s): Lawrence C. Marsh*+ and Amos Golan
Companies: University of Notre Dame and American University
Address: Dept. of Economics and Econometrics, Notre Dame, IN, 46556-5611,
Keywords: incomplete discrete response ; biased sample selection ; logistic/logit models ; eigenvalues and eigenvectors ; singular value decomposition ; missing-at-random nonresponse
Abstract:

Recent research using maximum likelihood methods in estimating missing categorical dependent variable values has produced promising but highly unstable results. Entropy and informational econometric methods offer an approach to the problem that is specifically designed to deal with ill-posed inverse problems to produce more stable and reliable estimates. The research literature on missing categorical response models generally assumes that the responses are missing at random after controlling for all relevant observable data. Our method corrects for systematic bias that may remain after controlling for observables. With relatively mild assumptions we are able to restore the full joint probabilities for both the complete and the incomplete responses.

  • 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