Extended Case-Control Designs for
Cost-Effective Translational Studies
Case-control designs are widely used to
assess relative risks of various diseases in epidemiology and many medical studies.
In recent clinical and translational studies, however, there are increasing
demands for cost-effective study designs for assessing both the relative and
absolute risks of disease progression and other adverse events. In this talk,
we will discuss some extended case-control designs that combine strengths of
the classical case-control and case-cohort study designs. Simple forms of
semi-parametric likelihood models are suggested for analyzing the data
collected from the study designs. Maximum likelihood estimates of the model
parameters can be calculated using existing or freely available software, and
are relatively straightforward to interpret by clinical investigators.
Numerical demonstrations are also discussed. (This talk is based on join work
with Shulian Shang at