Work sampling is an observational technique that produces counts representing the number of times that an individual has been observed performing each of several tasks. These data are collected using either systematic or random times of observation, and typically exhibit correlation between repeated observations on the same individual, with the degree of correlation being a function of the amount of time elapsed between measurements. Using several recently developed statistical techniques, we illustrate how it is possible to carry out analyses of these nominal outcomes that account for the correlation between repeated outcomes. We use description of a work sampling study to motivate the techniques and we compare empirically results from analyses based on several different underlying assumptions.