Modeling Placebo Response via Infinite Mixtures

• Activity Number: 644
• Type: Invited
• Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
• Sponsor: ENAR
• Author(s): Thaddeus Tarpey*+
• Companies: Wright State University
• Keywords: convolution ; EM algorithm ; finite mixture models ; maximum likelihood estimation

Abstract

Nonspecific treatment response, also known as placebo response, is ubiquitous in the treatment of mental illness, particularly in treating depression. The study of placebo effect is complicated because the factors that constitute nonspecific treatment effects are latent and not directly observed. A flexible infinite mixture model is introduced to model these nonspecific treatment effects. The infinite mixture model stipulates that the nonspecific treatment effects are continuous and this is contrasted with a finite mixture model that is based on the assumption that the nonspecific treatment effects are discrete. Data from a depression clinical trial is used to illustrate the model and to study the evolution of the placebo effect over the course of treatment.