A major legal issue in the United States for the past several years has been the tobacco industry's liability for health-care expenditures incurred because of its alleged misconduct beginning in the mid 1950's. Quantifying answers to such causal questions is a statistical enterprise, which has been especially active in the last quarter century. This presentation summarizes my formulation of a statistically valid approach for addressing the question, which generalizes the traditional epidemiological framework involving "confounders", "relative risks", and "attributable risks". Moreover, the framework provides an explicit statement of the key assumption underlying such estimation. Discussion of this assumption, how to make it plausible in practice, and the resultant demands on data will be presented. Also, the presentation will include a summary of current conclusions regarding the types of interventions that appear to be most successful at curtailing smoking, an issue of great concern to the public health community as well as a critical ingredient in the estimation of the effects of the tobacco industry's conduct.
Learning Objectives: TBA.
Keywords: Biostatistics, Smoking
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.