In judgement sampling, the researcher or some other "expert" uses his/her judgement in selecting the units from the population for study based on the population’s parameters.
This type of sampling technique might be the most appropriate if the population to be studied is difficult to locate or if some members are thought to be better (more knowledgeable, more willing, etc.) than others to interview. This determination is often made on the advice and with the assistance of the client. For instance, if you wanted to interview incentive travel organizers within a specific industry to determine their needs or destination preferences, you might find that not only are there relatively few, they are also extremely busy and may well be reluctant to take time to talk to you. Relying on the judgement of some knowledgeable experts may be far more productive in identifying potential interviewees than trying to develop a list of the population in order to randomly select a small number.
This approach is used when a sample is taken based on certain judgements about the overall population. The underlying assumption is that the investigator will select units that are characteristic of the population. The critical issue here is objectivity: how much can judgment be relied upon to arrive at a typical sample? Judgement sampling is subject to the researcher's biases and is perhaps even more biased than haphazard sampling. Since any preconceptions the researcher may have are reflected in the sample, large biases can be introduced if these preconceptions are inaccurate.
Statisticians often use this method in exploratory studies like pre-testing of questionnaires and focus groups. They also prefer to use this method in laboratory settings where the choice of experimental subjects (i.e., animal, human, vegetable) reflects the investigator's pre-existing beliefs about the population.