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Nonprobability sampling is a method of selecting cases from a population without the use of random selection. Random selection requires each case in a population to have an equal chance of being selected. Nonprobability sampling, in contrast, describes any method in which some cases have no chance for selection in the study. Nonprobability sampling is likely to occur when researchers do not know or do not have access to all cases in a target population, which frequently occurs in communication research. For example, it would be extremely difficult for each adult in a city to have the same chance of being selected for an online survey because it would require not only contact information for each person, but each adult to have Internet access, which is not necessarily the case for individuals who are homeless, living below the poverty level, or in extremely rural areas. Instead, researchers narrow the potential list of individuals through a variety of strategies. This entry discusses different types of nonprobability sampling, disadvantages of nonprobability sampling, and advantages of nonprobability sampling.

Types of Nonprobability Sampling

There are four main types of nonprobability sampling: convenience sampling, purposive sampling, respondent-assisted sampling, and quota sampling. While there are other types and variation within type, these four are commonly used in communication research.

Convenience Sampling

Convenience sampling (also called accidental, availability, or haphazard sampling) occurs when researchers use availability and convenience to identify potential cases for study. For example, a researcher may ask students in a large lecture university course to fill out a questionnaire. Research also utilizes convenience sampling when individuals can self-select into the study. For example, a person responds to a company’s social media post asking visitors to the site to respond to a survey.

Purposive Sampling

Researchers engage in purposive sampling (also called judgmental or purposeful sampling) when they select cases from a population based on specific characteristics or their knowledge of the target population. Often researchers will identify specific inclusion or exclusion criteria for study participation. For example, a researcher may want to interview leaders of a social movement, not just participants in the social movement. Thus, the researcher would first need to determine criteria that would help him or her identify leaders in the social movement and exclude others from consideration. Next, the researcher would contact social organizations to identify people who fit the criteria. Researchers may also select participants in specific communities because they are interested in groups that are highly represented in those communities. For example, researchers interested in communication disparities may only recruit participants in low-income counties in an attempt to increase the number of low-income participants.

Respondent-Assisted Sampling

Respondent-assisted sampling occurs when researchers ask participants to help them identify additional people from the target population. The two most common types of this sampling method are snowball sampling and network sampling. Both sampling techniques are very similar; researchers ask participants to identify other members of the target population (usually people who share similar characteristics) and provide contact information for those people. Respondent-assisted sampling is primarily used when the target population is difficult to identify and locate. For example, researchers might ask runaway teenagers for the contact information of other teenagers that have run away from home.

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