Sampling Techniques & Participant Recruitment Flashcards

A researcher wants to ensure that rural, suburban, and urban populations are proportionally represented in a national survey. Which sampling method is most appropriate?

Answer: Stratified random sampling

Stratified random sampling divides the population into subgroups (strata) and samples proportionally from each, ensuring representation of all geographic categories.

In cluster sampling, what is the primary unit of random selection?

Answer: Naturally occurring groups

Cluster sampling randomly selects naturally occurring groups (clusters) such as schools or neighborhoods, then surveys all or a sample of members within selected clusters.

Which condition makes snowball sampling particularly useful?

Answer: The population is hard to reach or identify

Snowball sampling is ideal when the target population is hidden or difficult to identify, such as undocumented immigrants or illicit drug users, where participants refer others.

A sampling frame that excludes certain segments of the target population will most likely result in:

Answer: Coverage error

Coverage error occurs when the sampling frame does not include all members of the target population, causing systematic exclusion and potential bias.

What distinguishes purposive sampling from probability sampling?

Answer: Purposive sampling relies on researcher judgment to select participants

Purposive sampling involves deliberate selection of participants based on specific characteristics deemed relevant to the research, rather than random selection.

A researcher mails surveys to every 10th name on a voter registration list. This is an example of:

Answer: Systematic sampling

Systematic sampling selects every nth element from a list after a random starting point, making it efficient when a complete ordered list is available.

Which type of error is introduced when participants who respond to a survey differ systematically from those who do not respond?

Answer: Nonresponse bias

Nonresponse bias occurs when respondents and non-respondents differ on key variables, making survey results unrepresentative of the full target population.