Bayesian Nonlinear Regression for Neutralization Assays Using 4- and 5-Parameter Growth Curves

• Activity Number: 321
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): James Slaughter*+ and John T. Bates and James E. Crowe
• Companies: Vanderbilt University and Vanderbilt University and Vanderbilt University
• Keywords: non-linear ; growth ; bayes

Abstract

In a neutralization assay, interest lies in estimating the concentration at which the plaque count is reduced to the pth percent of control. This is typically accomplished by assuming the control counts are fixed and known, fitting a 4-parameter logistic growth curve to observed counts and log-transformed concentrations, and back transforming the fitted model results to estimate the concentration of interest. We described a Bayesian non-linear regression model for joint estimation of control counts and the non-linear dose-response curve. Furthermore, we compare the fit of several different 5-parameter growth curve models that allow for non-symmetry about the inflection point of the curve. Finally, the 5-parameter models are compared to an alternative approach in which we consider the power family of transformations for concentration to achieve symmetry while fitting a 4-parameter model.