Foremost, the random purposeful sample is a purposeful sample, meaning the researchers employing sampling decided to choose a specific group of people or objects within a population to analyze. However, the researchers still have the intent of describing the population as a whole. The chosen group is often the one that can offer the most information to the researchers. For example, a random purposeful sample regarding voting behavior may include people from every socio-economic status, and thus may target only areas where there is high socio-economic heterogeneity.
A random purposeful sample is random at the same time it is purposeful. This process happens in stages. First, a subgroup of the population is determined, as it is for normal purposeful sampling. Second, a random sample is pulled from that subgroup. Essentially, the sample is a random sample, not of the population, but of a sub-population. Thus, for a voting random purposeful sample, the randomization of subjects would likely take place after researchers have gathered a list of residents living in economically heterogeneous areas.
The advantages of random purposeful sampling include some of the advantages of random sampling and purposeful sampling. Like purposeful sampling, random purposeful sampling allows researchers to pull information-dense data points from the population, giving them more ability to make interesting inferences. Like random sampling, random purposeful sampling increases the statistical validity of the sample, which helps in publishing findings in reputable journals.
Random purposeful samples are not perfect. Like purposeful samples, and unlike random samples, they cannot generalize to the overall population. This is an important disadvantage, because it limits the interpret-ability of results. In addition, the choice of the subgroup of the population is somewhat subjective, which is problematic, because the implication of a random sample is that it is objective, and other researchers should be able to duplicate findings.