Logistatic Dose-response Models under Compliance Measurement Error for Some Problems in Inhalation Toxicology

MARIO CHEN MOK: Logistic Dose-Response Models under Compliance Measurement Error for some Problems in Inhalation Toxicology. (Under the direction ofDr. PRANAB KUMAR SEN.) In a classical measurement error model, true regressors, though unknown, vary stochastically around' the specified dose level. In inhalation toxicology problems, however, it is reasonable to assumed that the administered dose is not completely absorbed into the system because a portion of the dose is either metabolized or deflected by the different mechanisms in the body. This results in stochastic compliance of the administered dose, typically being smaller in magnitude. We introduce a model· for compliance based on a Beta distribution. Logistic models are among the most widely used models in dose-response analysis. In this research, we are primarily interested in stochastic compliance of various types, and the study of its impact on logistic models. We consider suitable adjustments for compliance of the administered doses, and develop appropriate approximate models that are likely to have reduced bias and more efficient statistical conclusions than in logistics models that ignore such measurement error. We develop compliance-adjusted models for the classical logistic model, a bivariate logistic model, and a segmented logistic model. These compliance-adjusted models are categorized into three types: (i) Low (or near zero) dose levels, (ii) moderate dose levels, and (iii) high dose levels. The low dose setting is appropriate 1II