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Summary Various distance-based methods of testing for randomness in a population of spatially distributed events are described. Special emphasis is placed upon preliminary analysis in which the complete enumeration of the events within the study area is not available. Analytical progress in assessing the power of the techniques against extremes of aggregation and regularity is reviewed and the results obtained from the Monte Carlo simulation of more realistic processes are presented. It is maintained that the method of T-square sampling can help to provide quick and informative results and is especially suited to large populations. Some comments on contiguous quadrat methods are made.
Diggle et al. (Wed,) studied this question.