ABSTRACT
Probability models have proven to be very useful in the quantitative study of health care phenomena but their successful implementation requires the user to understand the underlying event whose probability is to be obtained. The researcher must often examine the event from a different and new perspective, while simultaneously grasping the nature of the available probability models. Only in this way can the worker adapt the underlying event and mold the probability model to generate relevant probabilities for events of interest. It is this joint process that makes the application of probability theory somewhat of an art. A useful tool for modeling public health problems of interest is the use of the theory of runs. After a brief review of run theory, this chapter will build a bridge to run theory with difference equations. This work will span two chapters, and introduce two models, the Ri,k(n) model and the T[K,L](n) model. Each of these models will be valuable in using difference equations to generate probability distributions of interest to public health issues that can be considered as a “run” of specific events.
