Which are the three forms of nonprobability sampling?

Study for the ACVPM Epidemiology and Biostatistics Exam. Prepare with flashcards and multiple choice questions, with hints and explanations for each. Be exam-ready!

Multiple Choice

Which are the three forms of nonprobability sampling?

Explanation:
Nonprobability sampling relies on the researcher’s judgment or accessibility rather than random selection, so not every unit has a known chance of inclusion. Three forms commonly labeled as nonprobability sampling are consecutive sampling, convenience sampling, and judgmental (purposive) sampling. Consecutive sampling enrolls every eligible subject as they become available within a defined period or setting, which reduces selective bias but still gives no known probability of inclusion. Convenience sampling picks units based on ease of access, which is fast but introduces substantial selection bias because the sample may not reflect the broader population. Judgmental or purposive sampling uses the researcher’s expertise to select cases that are especially informative or representative of the phenomenon under study, prioritizing depth over representativeness. In contrast, the other options mix methods that are typically probability-based—such as simple random, systematic, stratified, cluster, or multistage designs—where each unit has a known chance of selection and statistical inference about the population can be made.

Nonprobability sampling relies on the researcher’s judgment or accessibility rather than random selection, so not every unit has a known chance of inclusion. Three forms commonly labeled as nonprobability sampling are consecutive sampling, convenience sampling, and judgmental (purposive) sampling. Consecutive sampling enrolls every eligible subject as they become available within a defined period or setting, which reduces selective bias but still gives no known probability of inclusion. Convenience sampling picks units based on ease of access, which is fast but introduces substantial selection bias because the sample may not reflect the broader population. Judgmental or purposive sampling uses the researcher’s expertise to select cases that are especially informative or representative of the phenomenon under study, prioritizing depth over representativeness. In contrast, the other options mix methods that are typically probability-based—such as simple random, systematic, stratified, cluster, or multistage designs—where each unit has a known chance of selection and statistical inference about the population can be made.

Subscribe

Get the latest from Passetra

You can unsubscribe at any time. Read our privacy policy