Convenience Sampling in Research

Convenience Sampling

• A non-probabilistic sampling technique where researchers select individuals or items that are easily accessible or convenient to include in their study.
• May introduce bias since it may not accurately represent the population of interest.
• Example: Recruiting patients who happen to be available during their visits in a hospital, which may not capture the experiences of patients who are unable to visit the hospital regularly or who receive care elsewhere.

Snowball Sampling

• A non-probability strategy used in research studies where current study participants select potential future subjects from among their friends.
• Frequently used in disciplines like sociology, anthropology, and epidemiology, especially when it's challenging to locate or contact a particular community for research.
• Begins with a small group of people who fit the researcher's requirements, and has its limits, so researchers often combine it with other sampling techniques or proceed with caution when interpreting data.
• Three types of snowball sampling methods: Linear, Exponential non-discriminative, and Exponential discriminative.
• Example: Studying the experiences of illegal immigrants in a certain city, where traditional sample techniques may have trouble reaching this demographic.

Good Sampling

• Ensures that the chosen subset accurately represents the larger population while minimizing bias, leading to more relevant findings and decisions.
• Has four qualities: randomness, representativeness, adequacy, and reliability.
• Random sampling from a population guarantees that each participant has an equal probability of being selected, reducing bias and enabling population-wide generalization.
• Purposive sampling involves the conscious selection of participants based on pre-established criteria, and may not be as statistically representative as random sampling, but can be useful for concentrating attention on specific features or interest groups.
• The choice between random and purposive sampling depends on the expected degree of generalizability, the study objectives, and the resources available.