JSM 2005 Online Program

Abstract #304687

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:	51
Type:	Invited
Date/Time:	Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor:	General Methodology
Abstract - #304687
Title:	Testing Equality of Ordered Means in the General Linear Model
Author(s):	Michael P. McDermott*+
Companies:	University of Rochester
Address:	Department of Biostatistics and Comp Biology, Rochester, NY, 14642,
Keywords:	Combining dependent p-values ; Fisher's combination method ; Order restricted inference ; Partial order
Abstract:	Hypothesis-testing problems involving order constrained means arise frequently in practice. The standard approach to this problem in the one-way layout is the likelihood ratio test. In many practical settings, such as a randomized clinical trial, it is useful to include covariates in the primary statistical model. Likelihood ratio tests for equality of ordered means that incorporate covariate adjustment are complex and rarely applied in practice because of difficulties in their implementation. In this paper, a new test is proposed based on multiple contrasts among the adjusted group means. The P-values associated with these contrasts are, in general, dependent. An overall significance test is carried out using Fisher's statistic to combine the dependent P-values arising from these contrasts. The contrasts can be chosen to yield a test with high power, for alternatives at a fixed distance from the null hypothesis, throughout the restricted parameter space. The test is generally easy to implement for a variety of partial order restrictions. An example from a randomized clinical trial is used to illustrate the proposed test.

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