JSM 2005 Online Program

Abstract #304547

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

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	450
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #304547
Title:	Not Worth the Effort: Balanced Ranked Set Sampling and Random Predictor OLS Regression
Author(s):	Elizabeth J. Murff*+ and Thomas W. Sager
Companies:	Eastern Washington University and The University of Texas at Austin
Address:	College of Business and Public Administration, Spokane, WA, 99202, United States
Keywords:	ranked set sampling ; balanced allocation ; judgement ranking ; random predictor ; regression ; equivalent sample size
Abstract:	Contrary to the published results on fixed predictors, OLS regression---balanced ranked set sampling---offers at most only small improvement in the relative efficiency of the slope estimator in a random predictors OLS regression. The maximum improvement offered by balanced ranked set sampling at any sample size is equivalent to having at most three additional sampling units in a simple random sample. Statistical theory and simulation confirm these limitations. An anticipated application of balanced ranked set sampling to the problem of estimating mercury contamination from fish length was canceled in light of these results, as the extra sampling cost was judged not worth the slight gain.

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