JSM 2005 Online Program

Abstract #304405

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:	518
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Government Statistics
Abstract - #304405
Title:	Approximate Power Curves for Detecting Changes in Trend for Complex Surveys
Author(s):	Maya Sternberg*+
Companies:	Centers for Disease Control and Prevention
Address:	1600 Clifton RD MS E63, Atlanta, GA, 30333, United States
Keywords:	power ; complex survey ; NCHS ; trends
Abstract:	The National Center for Health Statistics (NCHS) conducts several nationwide surveys using complex survey methods. The Centers for Disease Control and Prevention has used some of these data sources for their annual surveillance report to monitor trends in pelvic inflammatory disease (PID) throughout the past 10 years. Often, the design effect of a survey is used to provide general guidance about the power of a complex survey to detect changes relative to a simple random survey. This talk will outline an alternative approach where a test statistic will be combined with the results of the generalized variance curve published in the NCHS documentation to calculate the approximate power a survey may have to detect changes over time. This information can be used to gauge whether such surveys are practical and useful to monitor annual changes for a given health condition, or whether data from several annual surveys should be aggregated to achieve reasonable power to test for differences. The specific example of PID will be used and the observed power will be compared with the results obtained using the generalized variance curve information.

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