Abstract #301074


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 2002 Program page



JSM 2002 Abstract #301074
Activity Number: 320
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section*
Abstract - #301074
Title: Comparison of Methods to Analyze Coarse Immunogenicity Data
Author(s): William Wang*+ and Eric Zhi and Ivan Chan
Affiliation(s): Merck Research Laboratories and University of Minnesota and Merck Research Laboratories
Address: 785 Jolly Road, Building C, Blue Bell, Pennsylvania, 19422, US
Keywords: coarse data ; immunogenicity ; maximum likelihood ; multiple imputation
Abstract:

Coarse data arise in vaccine clinical trials when an immunologic response is measured by a serial dilution assay, which may give a range of response instead of the exact value in the absence of standard calibration curve. A conventional method treats the lower limit of the range as the exact value in estimating the population mean immunologic response or in treatment comparisons. Ignoring the data coarseness, this method may cause bias and underestimation of the variance of parameter estimates. In this talk, we explore some alternative methods for analyzing coarse data, including the maximum likelihood (ML) method and the multiple imputation method. We carried out simulation studies to compare the performance of these methods under the log-normality assumption. The results suggest that the ML method for coarse data performs best under a wide variety of parameter settings.


  • 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 2002 program

JSM 2002

For information, contact meetings@amstat.org or phone (703) 684-1221.

If you have questions about the Continuing Education program, please contact the Education Department.

Revised March 2002