Nonprobability Sampling

Probability Sampling

There are many different types of probability sampling procedures. More common ones include simple, systematic, stratified, multistage, and cluster sampling. Probability sampling allows one to have confidence that the results are accurate and unbiased, and it allows one to estimate how precise the data are likely to be. The data from a properly drawn sample are superior to data drawn from individuals who just show up at a meeting or perhaps speak the loudest and convey their personal thoughts and sentiments. The critical issues in sampling include whether to use a probability sample, the sampling frame (the set of people that have a chance of being selected and how well it corresponds to the population studied), the size of the sample, the sample design (particularly the [Page 922]strategy used to sample people, schools, households, etc.), and the response rate. The details of the sample design, including size and selection procedures, influence the precision of sample estimates regarding how likely the sample is to approximate population characteristics. The use of standardized measurement tools and procedures also helps to assure comparable responses.

Nonprobability Sampling

Nonprobability sampling is conducted without the knowledge about whether those chosen in the sample are representative of the entire population. In some instances, the researcher does not have sufficient information about the population to undertake probability sampling. The researcher might not even know who or how many people or events make up the population. In other instances, nonprobability sampling is based on a specific research purpose, the availability of subjects, or a variety of other nonstatistical criteria. Applied social and behavioral researchers often face challenges and dilemmas in using a random sample, because such samples in a real-world research are “hard to reach” or not readily available. Even if researchers have contact with hard to reach samples, they might be unable to obtain a complete sampling frame because of peculiarities of the study phenomenon. This is especially true when studying vulnerable or stigmatized populations, such as children exposed to domestic violence, emancipated foster care youth, or runaway teenagers. Consider for instance the challenges of surveying adults with the diagnosis of paranoid personality disorder. This is not a subgroup that is likely to agree to sign a researcher's informed consent form, let alone complete a lengthy battery of psychological instruments asking a series of personal questions.

Applied researchers often encounter other practical dilemmas when choosing a sampling method. For instance, there might be limited research resources. Because of limitations in funding, time, and other resources necessary for conducting large-scale research, researchers often find it difficult to use large samples. Researchers employed by a single site or agency might be unable to access subjects served by other agencies located in other sites. It is not a coincidence that recruiting study subjects from a single site or agency is one of the most popular methods among studies using nonprobability procedures. The barriers preventing a large-scale multisite collaboration among researchers can be formidable and difficult to overcome.

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