Abstract A3: Design and model for breast cancer literacy outcomes among medically underserved females in Michigan

Statistical theory requires that analysis of study outcomes be conducted conditional on the design process. Ignoring this process may result in severely biased estimates, leading to false inferences, especially when the outcome variable is associated with design variables. We propose in this paper a class of hierarchical models to investigate the dependence between the design process and the study outcomes of primary interest. We discuss a fully parametric and a semiparametric formulation of the hypothesized model and propose the EM algorithm to obtain maximum likelihood estimates. Our numerical results show that the semiparametric approach outperforms the fully parametric model with respect to some key features of the model. The methodology is used to gain insight into the mechanism that generates breast cancer literacy outcomes in a study conducted among medically underserved females in Michigan.

Citation Information: Cancer Epidemiol Biomarkers Prev 2010;19(10 Suppl):A3.