External validity is fundamental to veterinary diagnostic investigation, reflecting the accuracy with which sample results can be extrapolated to a broader population of interest. Probability sampling methods are routinely used during the collection of samples from populations, specifically to maximize external validity. Nonprobability sampling (e.g., of blood samples collected as part of routine surveillance programs or laboratory submissions) may provide useful data for further posthoc epidemiological analysis, adding value to the collection and submission of samples. As the sample has already been submitted, the analyst or investigator does not have any control over the sampling methodology, and hence external validity as routine probability sampling methods may not have been employed. The current study describes several Geographic Information System (GIS) and non-GIS methods, applied posthoc, to assess the external validity of samples collected using both probability and nonprobability sampling methods. These methods could equally be employed for inspecting other datasets. Mapping was conducted using ArcView 9.1. Based on this posthoc assessment, results from the random field sample could provide an externally valid, albeit relatively imprecise, estimate of national disease prevalence, of disease prevalence in 3 of the 4 provinces (all but Ulster, in the north and northwest, where sample size was small), and in beef and dairy herds. This study provides practical methods for examining the external validity of samples postcollection.